Triple
T7616075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian McCaffrey |
E172363
|
entity |
| Predicate | NCAASingleSeasonAllPurposeYardsRecord |
P78134
|
FINISHED |
| Object | set in 2015 season |
—
|
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: set in 2015 season | Statement: [Christian McCaffrey, NCAASingleSeasonAllPurposeYardsRecord, set in 2015 season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: NCAASingleSeasonAllPurposeYardsRecord Context triple: [Christian McCaffrey, NCAASingleSeasonAllPurposeYardsRecord, set in 2015 season]
-
A.
NFLAllTimeRushingYardsLeader
Indicates that the subject is the player who has accumulated the most career rushing yards in NFL history.
-
B.
singleSeasonRushingYardsRecord
Indicates the record-setting total number of rushing yards accumulated by a player in a single season.
-
C.
singleSeasonRushingTouchdownsRecord
Indicates that an entity holds the record for the most rushing touchdowns scored in a single season.
-
D.
nflAllTimePointsLeader
Indicates that the subject is the player who holds the record for the most career points scored in NFL history.
-
E.
careerReceivingYards
Indicates the total number of yards a player has gained by receiving the ball over the course of their entire career.
- 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_69c6994f50808190ba228764bb422417 |
completed | March 27, 2026, 2:50 p.m. |
| NER | Named-entity recognition | batch_69c6fe73ff7c8190ab1218d97b37416d |
completed | March 27, 2026, 10:02 p.m. |
| PD | Predicate disambiguation | batch_69c6f4e725a88190b1f05dd224f7f4f2 |
completed | March 27, 2026, 9:21 p.m. |
| PDg | Predicate description generation | batch_69c6fe7323b0819081664662d2f26937 |
completed | March 27, 2026, 10:02 p.m. |
Created at: March 27, 2026, 3:55 p.m.