Triple
T14792104
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thanksgiving games |
E347680
|
entity |
| Predicate | thirdGameType |
P116124
|
FINISHED |
| Object | primetime game |
—
|
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: primetime game | Statement: [Thanksgiving games, thirdGameType, primetime game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: thirdGameType Context triple: [Thanksgiving games, thirdGameType, primetime game]
-
A.
ballGameType
Indicates the specific kind or category of ball game associated with an event or activity.
-
B.
typicalGame
Indicates a relationship where one entity is characterized as a standard, representative, or commonly occurring example of a game for the other entity or context.
-
C.
primaryGameType
Indicates the main category or type of game with which an entity is primarily associated.
-
D.
thirdStageType
Indicates the specific kind or classification of a third stage within a multi-stage process or structure.
-
E.
officiatedGameType
Indicates the type or category of game that an official (e.g., referee or umpire) presided over.
- 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_69d822ea8b7c819097dfadf3d45545e6 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69decd5d134c819080ee788b2e34163a |
completed | April 14, 2026, 11:27 p.m. |
| PD | Predicate disambiguation | batch_69de8c090d1081909b5a9bf437499d6c |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de90c5e3a08190868680b081308c1d |
completed | April 14, 2026, 7:08 p.m. |
Created at: April 10, 2026, 1:31 a.m.