Triple
T36946637
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyson Gay |
E913929
|
entity |
| Predicate | timeIn100MetresEqualled |
P186764
|
FINISHED |
| Object | third-fastest ever at time of performance |
—
|
LITERAL FINISHED |
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: third-fastest ever at time of performance | Statement: [Tyson Gay, timeIn100MetresEqualled, third-fastest ever at time of performance]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeIn100MetresEqualled Context triple: [Tyson Gay, timeIn100MetresEqualled, third-fastest ever at time of performance]
-
A.
hasRunSub10Seconds100m
Indicates that the subject has completed a 100-meter sprint in under 10 seconds.
-
B.
goldMedalWinnerIn men's 100 metres
Indicates that the subject is the athlete who won the gold medal in the men's 100 metres event in a specified competition.
-
C.
quarterMileTime
Indicates the time it takes an entity (typically a vehicle or runner) to travel a quarter of a mile.
-
D.
personalBest400m
Indicates that the related 400-meter race performance is the best time or result the person has ever achieved in that event.
-
E.
legRunner
Indicates that an entity functions as a runner or moving component that operates in conjunction with a leg or leg-like structure.
- F. None of above. chosen
Provenance (4 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_69f76e8b28848190abd81fe7a7374910 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fa0a7b00948190a257273d9968c5d7 |
completed | May 5, 2026, 3:19 p.m. |
| PD | Predicate disambiguation | batch_69f9fec9c9488190ae2a349651a02782 |
completed | May 5, 2026, 2:29 p.m. |
| PDg | Predicate description generation | batch_69fa0a799b9081909bfa8293a22c4b00 |
completed | May 5, 2026, 3:19 p.m. |
Created at: May 3, 2026, 4:13 p.m.