Triple
T11594270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gale Sayers |
E274960
|
entity |
| Predicate | scoredTouchdownsInSingleGame |
P14053
|
FINISHED |
| Object | 6 |
—
|
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: 6 | Statement: [Gale Sayers, scoredTouchdownsInSingleGame, 6]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scoredTouchdownsInSingleGame Context triple: [Gale Sayers, scoredTouchdownsInSingleGame, 6]
-
A.
threwTouchdownPassesInSingleSeason
Indicates that one entity (typically a quarterback) successfully threw a certain number of touchdown passes during a single football season.
-
B.
singleSeasonTotalTouchdownsRecord
Indicates the record-setting highest number of touchdowns scored by an entity within a single season.
-
C.
touchdownsScored
chosen
Indicates the number of touchdowns that an entity has scored.
-
D.
rushingTouchdownsInSeason
Indicates the number of rushing touchdowns a player scores during a single season.
-
E.
singleSeasonRushingTouchdownsRecord
Indicates that an entity holds the record for the most rushing touchdowns scored in a single season.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8946790d08190924d60bb4b523250 |
completed | April 10, 2026, 6:10 a.m. |
| PD | Predicate disambiguation | batch_69d85dd20d188190863d1190d4c16048 |
completed | April 10, 2026, 2:17 a.m. |
Created at: April 8, 2026, 9:38 p.m.