Triple
T8677961
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jeff Garcia |
E205961
|
entity |
| Predicate | threwTouchdownPassesInSingleSeason |
P84439
|
FINISHED |
| Object | 30 (2000 NFL 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: 30 (2000 NFL season) | Statement: [Jeff Garcia, threwTouchdownPassesInSingleSeason, 30 (2000 NFL season)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: threwTouchdownPassesInSingleSeason Context triple: [Jeff Garcia, threwTouchdownPassesInSingleSeason, 30 (2000 NFL season)]
-
A.
passingTouchdownsCareer
Indicates the total number of touchdown passes a player has thrown over the course of their entire career.
-
B.
rushingTouchdownsInSeason
Indicates the number of rushing touchdowns a player scores during a single season.
-
C.
NFLTouchdownPasses
Indicates that a player successfully throws a pass that results in a touchdown being scored in an NFL game.
-
D.
singleSeasonRushingTouchdownsRecord
Indicates that an entity holds the record for the most rushing touchdowns scored in a single season.
-
E.
singleSeasonTotalTouchdownsRecord
Indicates the record-setting highest number of touchdowns scored by an entity within a single season.
- 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_69ca83529a9c8190b5c075b4f14636ed |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc4ae6d19c8190be003f7901c0468d |
completed | March 31, 2026, 10:29 p.m. |
| PD | Predicate disambiguation | batch_69cc4567b5c881908d9ec5dcfc783fac |
completed | March 31, 2026, 10:06 p.m. |
| PDg | Predicate description generation | batch_69cc4ae517108190a71a86349815f4ce |
completed | March 31, 2026, 10:29 p.m. |
Created at: March 30, 2026, 6:32 p.m.