Triple
T32116108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Jim Taylor |
E820241
|
entity |
| Predicate | rushingTouchdownsIn1962Season |
P70224
|
FINISHED |
| Object | 19 |
—
|
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: 19 | Statement: [Jim Taylor, rushingTouchdownsIn1962Season, 19]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rushingTouchdownsIn1962Season Context triple: [Jim Taylor, rushingTouchdownsIn1962Season, 19]
-
A.
rushingTouchdownsInSeason
chosen
Indicates the number of rushing touchdowns a player scores during a single season.
-
B.
rushingTouchdownsInRookieSeason
Indicates the number of rushing touchdowns a player scored during their rookie season.
-
C.
touchdownsScored
Indicates the number of touchdowns that an entity has scored.
-
D.
hasNFLRushingTouchdowns
Indicates that an entity (typically a player or team) has scored one or more rushing touchdowns in NFL games.
-
E.
rushingYardsRecord
Indicates that an entity holds or represents the record for the greatest number of rushing yards achieved in a specified context (such as a game, season, or career).
- 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_69f3490209c881908ec0241476715f15 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6b967d5308190bbb66d0a8dd52612 |
completed | May 3, 2026, 2:56 a.m. |
| PD | Predicate disambiguation | batch_69f6b6293188819080d5041ca0adb969 |
completed | May 3, 2026, 2:42 a.m. |
Created at: May 1, 2026, 12:28 a.m.