Triple
T12514698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | GNU As |
E299165
|
entity |
| Predicate | supportsTarget |
P5090
|
FINISHED |
| Object |
TilePro
TilePro is a family of many-core VLIW processors from Tilera, designed for highly parallel, scalable computing in embedded and networking applications.
|
E986423
|
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: TilePro | Statement: [GNU As, supportsTarget, TilePro]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TilePro Context triple: [GNU As, supportsTarget, TilePro]
-
A.
Tile IR
Tile IR is an intermediate representation used within the PlaidML machine learning compiler to express and optimize tensor computations across diverse hardware backends.
-
B.
Tiler
Tiler is the first name of Tiler Peck, a renowned American ballet dancer and principal with the New York City Ballet.
-
C.
Grand Tiler
Grand Tiler is a senior Masonic lodge officer responsible for guarding the entrance and ensuring the privacy and security of lodge meetings.
-
D.
Kachelotplate
Kachelotplate is a small, uninhabited sandbank island in the Wadden Sea off the coast of East Frisia in northwestern Germany.
-
E.
Tapeta
Tapeta is a town in northeastern Liberia known as the hometown of several prominent Liberian political figures, including warlord-turned-politician Prince Johnson.
- 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: TilePro Triple: [GNU As, supportsTarget, TilePro]
Generated description
TilePro is a family of many-core VLIW processors from Tilera, designed for highly parallel, scalable computing in embedded and networking applications.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TilePro Target entity description: TilePro is a family of many-core VLIW processors from Tilera, designed for highly parallel, scalable computing in embedded and networking applications.
-
A.
Tile IR
Tile IR is an intermediate representation used within the PlaidML machine learning compiler to express and optimize tensor computations across diverse hardware backends.
-
B.
Tiler
Tiler is the first name of Tiler Peck, a renowned American ballet dancer and principal with the New York City Ballet.
-
C.
Grand Tiler
Grand Tiler is a senior Masonic lodge officer responsible for guarding the entrance and ensuring the privacy and security of lodge meetings.
-
D.
Kachelotplate
Kachelotplate is a small, uninhabited sandbank island in the Wadden Sea off the coast of East Frisia in northwestern Germany.
-
E.
Tapeta
Tapeta is a town in northeastern Liberia known as the hometown of several prominent Liberian political figures, including warlord-turned-politician Prince Johnson.
- 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_69d6ada5cdd48190860d9ce30aff69be |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541e752c8190bf12d2b5a37b53df |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64bbd58b88190baeb99380babf64f |
completed | May 2, 2026, 7:08 p.m. |
| NEDg | Description generation | batch_69f64ce1b0ec8190bcbd245255e548b5 |
completed | May 2, 2026, 7:13 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f64db823bc819098152a96db960b10 |
completed | May 2, 2026, 7:17 p.m. |
Created at: April 8, 2026, 9:57 p.m.