Triple
T21301499
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eunice Barber |
E525074
|
entity |
| Predicate | personalBestLongJumpMetres |
P143653
|
FINISHED |
| Object | 7.05 |
—
|
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: 7.05 | Statement: [Eunice Barber, personalBestLongJumpMetres, 7.05]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: personalBestLongJumpMetres Context triple: [Eunice Barber, personalBestLongJumpMetres, 7.05]
-
A.
personalBest
Indicates that one entity represents the best performance or achievement ever attained personally by another entity.
-
B.
personalBestMarathon
Indicates that the associated marathon performance is the best (fastest or highest-achieving) marathon result attained by the person in question.
-
C.
personalBestMarathonYear
Indicates the year in which an entity achieved their personal best performance in a marathon.
-
D.
leapHeight
Indicates the vertical distance an entity reaches when it jumps or leaps.
-
E.
olympicBestResult
Indicates the best performance or highest achievement an entity has attained in Olympic competition.
- 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_69e0b517e6748190850d6f6ddf323d69 |
completed | April 16, 2026, 10:08 a.m. |
| NER | Named-entity recognition | batch_69e7385cd6308190bf300494833b048f |
completed | April 21, 2026, 8:42 a.m. |
| PD | Predicate disambiguation | batch_69e61612ab748190a72b8703b938abcb |
completed | April 20, 2026, 12:03 p.m. |
| PDg | Predicate description generation | batch_69e6190163448190a2404b396215c686 |
completed | April 20, 2026, 12:16 p.m. |
Created at: April 16, 2026, 4:05 p.m.