Triple
T12697102
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1959 NFL Championship |
E303362
|
entity |
| Predicate | pointsByWinner |
P7114
|
FINISHED |
| Object | 31 |
—
|
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: 31 | Statement: [1959 NFL Championship, pointsByWinner, 31]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsByWinner Context triple: [1959 NFL Championship, pointsByWinner, 31]
-
A.
pointsLeader
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
-
B.
winnerCount
Indicates the number of entities that are designated as winners in a given context or event.
-
C.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
D.
winnerPoints
chosen
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
E.
pointsClassificationWinner
Indicates that the subject is the winner of a competition or ranking based on accumulated points classification.
- F. None of above.
Provenance (3 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_69d7bdef90d48190b46b88270e780946 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d962a32c6481908ddaddae4ea267bf |
completed | April 10, 2026, 8:50 p.m. |
| PD | Predicate disambiguation | batch_69d960be63f081908a5ef5ef17a311bf |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:22 p.m.