Triple
T7432982
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrell Davis |
E171535
|
entity |
| Predicate | thousandYardRushingSeasons |
P66740
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Terrell Davis, thousandYardRushingSeasons, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thousandYardRushingSeasons Context triple: [Terrell Davis, thousandYardRushingSeasons, 4]
-
A.
1000YardRushingSeasons
chosen
Indicates that a player has achieved one or more seasons in which they rushed for at least 1,000 yards.
-
B.
rushingYards
Indicates the number of yards a player gains by running the ball on rushing plays.
-
C.
singleSeasonRushingYardsRecord
Indicates the record-setting total number of rushing yards accumulated by a player in a single season.
-
D.
singleSeasonRushingTouchdownsRecord
Indicates that an entity holds the record for the most rushing touchdowns scored in a single season.
-
E.
NFLAllTimeRushingYardsLeader
Indicates that the subject is the player who has accumulated the most career rushing yards in NFL history.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f325ea908190b668fd4ce646f1e6 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f038582c8190bac77c9b5a34b862 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:12 p.m.