Triple
T30859626
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mel Gray |
E786023
|
entity |
| Predicate | returnTouchdownsInNFL |
P180729
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Mel Gray, returnTouchdownsInNFL, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: returnTouchdownsInNFL Context triple: [Mel Gray, returnTouchdownsInNFL, multiple]
-
A.
careerNFLTouchdowns
Indicates the total number of touchdowns a player has scored over the course of their NFL career.
-
B.
touchdownsScored
Indicates the number of touchdowns that an entity has scored.
-
C.
hasNFLRushingTouchdowns
Indicates that an entity (typically a player or team) has scored one or more rushing touchdowns in NFL games.
-
D.
ledNFLInPassingTouchdowns
Indicates that the subject was the league leader in passing touchdowns in the NFL for a given season or time period.
-
E.
NFLTouchdownPasses
Indicates that a player successfully throws a pass that results in a touchdown being scored in an NFL game.
- 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_69f224b91c14819084e764832fe67a57 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
| PDg | Predicate description generation | batch_69f74c6fa6548190b03935f65429a24e |
completed | May 3, 2026, 1:23 p.m. |
Created at: April 29, 2026, 8:46 p.m.