Triple
T15439251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Graham Gooch |
E369853
|
entity |
| Predicate | yearOfHighestTestScore |
P118793
|
FINISHED |
| Object | 1990 |
—
|
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: 1990 | Statement: [Graham Gooch, yearOfHighestTestScore, 1990]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: yearOfHighestTestScore Context triple: [Graham Gooch, yearOfHighestTestScore, 1990]
-
A.
highestTestScore
Indicates that one entity has achieved the greatest test score among a specified set or in a given context.
-
B.
highestTestScoreVenue
Indicates the venue at which an entity achieved its highest test score compared to all other venues.
-
C.
highestTestScoreOpponent
Indicates that the related entity is the opponent who achieved the highest test score among all considered opponents.
-
D.
lastRecordedIndividualYear
Indicates the calendar year in which the last known individual of a species or population was recorded.
-
E.
hasHighestPoints
Indicates that the subject entity possesses the greatest number of points compared to all relevant others in the given context.
- 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_69d85a19180081909925012fbf4e62a3 |
completed | April 10, 2026, 2:02 a.m. |
| NER | Named-entity recognition | batch_69e03eddf258819082679970b7d2b6af |
completed | April 16, 2026, 1:43 a.m. |
| PD | Predicate disambiguation | batch_69ded28276f481908c2038bb301e57cf |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded57005608190886cd01f640dfedb |
completed | April 15, 2026, 12:01 a.m. |
Created at: April 10, 2026, 3:21 a.m.