Triple
T7897885
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | gRPC |
E183379
|
entity |
| Predicate | supportsSerializationFormat |
P77631
|
FINISHED |
| Object |
FlatBuffers
FlatBuffers is an efficient cross-platform serialization library from Google designed for fast, memory-efficient data access without an unpacking step, commonly used in games, mobile, and high-performance services.
|
E696494
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: FlatBuffers | Statement: [gRPC, supportsSerializationFormat, FlatBuffers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: FlatBuffers Context triple: [gRPC, supportsSerializationFormat, FlatBuffers]
-
A.
Protocol Buffers
Protocol Buffers is a language-neutral, platform-neutral mechanism developed by Google for efficiently serializing structured data, commonly used for communication protocols and data storage.
-
B.
MessagePack
MessagePack is a compact, efficient binary serialization format designed to encode structured data for fast transmission and storage across different programming languages.
-
C.
BSON
BSON is a binary-encoded serialization format commonly used by MongoDB to store and transfer structured data efficiently while supporting additional data types beyond those in JSON.
-
D.
Apache Parquet
Apache Parquet is a columnar storage file format optimized for efficient data compression and query performance in big data processing frameworks such as Apache Hadoop and Apache Spark.
-
E.
FBX
FBX is a widely used 3D asset exchange file format that supports complex geometry, materials, animation, and scene data across various graphics and game development applications.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: FlatBuffers Triple: [gRPC, supportsSerializationFormat, FlatBuffers]
Generated description
FlatBuffers is an efficient cross-platform serialization library from Google designed for fast, memory-efficient data access without an unpacking step, commonly used in games, mobile, and high-performance services.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: FlatBuffers Target entity description: FlatBuffers is an efficient cross-platform serialization library from Google designed for fast, memory-efficient data access without an unpacking step, commonly used in games, mobile, and high-performance services.
-
A.
Protocol Buffers
Protocol Buffers is a language-neutral, platform-neutral mechanism developed by Google for efficiently serializing structured data, commonly used for communication protocols and data storage.
-
B.
MessagePack
MessagePack is a compact, efficient binary serialization format designed to encode structured data for fast transmission and storage across different programming languages.
-
C.
BSON
BSON is a binary-encoded serialization format commonly used by MongoDB to store and transfer structured data efficiently while supporting additional data types beyond those in JSON.
-
D.
Apache Parquet
Apache Parquet is a columnar storage file format optimized for efficient data compression and query performance in big data processing frameworks such as Apache Hadoop and Apache Spark.
-
E.
FBX
FBX is a widely used 3D asset exchange file format that supports complex geometry, materials, animation, and scene data across various graphics and game development applications.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a296db8819084c620b12f77acb5 |
completed | March 31, 2026, 3:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5bb719a08190a0545a361f559bf7 |
completed | March 31, 2026, 5:29 a.m. |
| NEDg | Description generation | batch_69cb5f1f864c819086d3a2b04061ead0 |
completed | March 31, 2026, 5:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cb76aede388190a56e066c3302c35e |
completed | March 31, 2026, 7:24 a.m. |
Created at: March 30, 2026, 5:01 p.m.