Triple
T5925785
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ottis Anderson |
E131806
|
entity |
| Predicate | 1000YardRushingSeasons |
P66740
|
FINISHED |
| Object | 1979 |
—
|
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: 1979 | Statement: [Ottis Anderson, 1000YardRushingSeasons, 1979]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: 1000YardRushingSeasons Context triple: [Ottis Anderson, 1000YardRushingSeasons, 1979]
-
A.
rushingYards
Indicates the number of yards a player gains by running the ball on rushing plays.
-
B.
NFLAllTimeRushingYardsLeader
Indicates that the subject is the player who has accumulated the most career rushing yards in NFL history.
-
C.
careerRushingYards
Indicates the total number of rushing yards an entity has accumulated over the entire span of its career.
-
D.
nflRushingYardsLeader
Indicates the player who gained the most rushing yards in the NFL over a specified season or time period.
-
E.
careerRushingTouchdowns
Indicates the total number of rushing touchdowns a player has scored over the entire span of their 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03c8d579081909d7b97fc9014b5d7 |
completed | March 22, 2026, 7:01 p.m. |
Created at: March 22, 2026, 4 p.m.