Triple
T20106743
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gemini API |
E490196
|
entity |
| Predicate | accessMethod |
P5872
|
FINISHED |
| Object | gRPC |
—
|
NE NERFINISHED |
How this triple was built (2 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: gRPC | Statement: [Gemini API, accessMethod, gRPC]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: gRPC Context triple: [Gemini API, accessMethod, gRPC]
-
A.
gRPC
chosen
gRPC is a high-performance, open-source remote procedure call (RPC) framework developed by Google that uses HTTP/2 and protocol buffers to enable efficient, language-agnostic communication between services.
-
B.
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.
-
C.
KRPC
KRPC is a major Nigerian oil refinery and petrochemical complex located in Kaduna, involved in processing crude oil into refined petroleum products and petrochemicals.
-
D.
RPC
RPC is the commonly used abbreviation for the Dr. Rajendra Prasad Centre for Ophthalmic Sciences, a leading eye care and research institute in India.
-
E.
Dapr
Dapr is an open-source, portable, event-driven runtime that simplifies building resilient, microservices-based cloud-native applications.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69da62636cc08190982cc71733a17b8d |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e666dcb8d4819091889e19dd9137a6 |
completed | April 20, 2026, 5:48 p.m. |
Created at: April 11, 2026, 11:28 p.m.