Triple
T3904305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greatest Show on Turf offense |
E90567
|
entity |
| Predicate | seasonPointsRecordSet |
P52800
|
FINISHED |
| Object | 1999 |
—
|
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: 1999 | Statement: [Greatest Show on Turf offense, seasonPointsRecordSet, 1999]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: seasonPointsRecordSet Context triple: [Greatest Show on Turf offense, seasonPointsRecordSet, 1999]
-
A.
seasonRecord
Indicates the overall performance or results an entity achieved over the course of a specific season (e.g., wins, losses, or comparable outcome metrics).
-
B.
bestSeasonRecord
Indicates that one entity holds the best (most successful) season performance record among a set of entities, typically in a competitive or statistical context.
-
C.
seasonRecordWins
Indicates the number of games a team has won during a specific season.
-
D.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
-
E.
runnerUpRegularSeasonRecord
Indicates the regular season performance record (such as wins and losses) of the team that finished as runner-up.
- 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_69aed95d315881908cbf1bf4a7215fbf |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1abe2dc81909c18aeae9b286898 |
completed | March 9, 2026, 4:13 p.m. |
| PD | Predicate disambiguation | batch_69aee75cff148190b6d5979d17fae085 |
completed | March 9, 2026, 3:29 p.m. |
| PDg | Predicate description generation | batch_69aef1aada308190821a3dfa6af170b3 |
completed | March 9, 2026, 4:13 p.m. |
Created at: March 9, 2026, 3:22 p.m.