Triple
T13757568
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terrible Towel |
E330514
|
entity |
| Predicate | firstUseGameType |
P83650
|
FINISHED |
| Object | Pittsburgh Steelers home 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: Pittsburgh Steelers home game | Statement: [Terrible Towel, firstUseGameType, Pittsburgh Steelers home game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstUseGameType Context triple: [Terrible Towel, firstUseGameType, Pittsburgh Steelers home game]
-
A.
firstGamePlayed
Indicates the specific game that an entity participated in before any other, marking the earliest game in which it played.
-
B.
firstUsedInGame
chosen
Indicates the game in which something (such as an item, mechanic, or concept) was first introduced or appeared.
-
C.
primaryGameType
Indicates the main category or type of game with which an entity is primarily associated.
-
D.
hasGameType
Indicates that an entity (such as a game or match) is associated with a specific category or type of game.
-
E.
includesGameType
Indicates that one entity contains or supports a particular type or category of game.
- 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_69d81c573f288190aa2403d484fa3d49 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de022286b481908f8a801042743512 |
completed | April 14, 2026, 9 a.m. |
| PD | Predicate disambiguation | batch_69dbbe97846c819093b00ea117b64e0d |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 10:09 p.m.