Triple
T6001239
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1992 AFC Wild Card Game vs Buffalo Bills |
E133600
|
entity |
| Predicate | largestDeficitScore |
P11634
|
FINISHED |
| Object | Houston Oilers 35–3 Buffalo Bills |
—
|
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: Houston Oilers 35–3 Buffalo Bills | Statement: [1992 AFC Wild Card Game vs Buffalo Bills, largestDeficitScore, Houston Oilers 35–3 Buffalo Bills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: largestDeficitScore Context triple: [1992 AFC Wild Card Game vs Buffalo Bills, largestDeficitScore, Houston Oilers 35–3 Buffalo Bills]
-
A.
largestDeficitOvercome
chosen
Indicates the maximum deficit or point difference that was successfully overcome by one side to achieve a comeback in a contest or competition.
-
B.
lowestScore
Indicates that the associated value is the smallest (minimum) score among a set of scores.
-
C.
deficitQuarter
Indicates that an entity experienced a financial deficit during a specific fiscal quarter.
-
D.
loserScore
Indicates the number of points or score achieved by the losing participant in a competitive event or comparison.
-
E.
recordHighScoringForWinner
Indicates that a record is kept of the highest score achieved by the winning entity in a given context or event.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04ee7c0e08190a6e78969448b070a |
completed | March 22, 2026, 8:19 p.m. |
| PD | Predicate disambiguation | batch_69c049e152e88190979ab80cb9b50321 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:05 p.m.