Triple
T34687006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington Generals |
E890779
|
entity |
| Predicate | typicalGamePurpose |
P205522
|
FINISHED |
| Object | entertainment |
—
|
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: entertainment | Statement: [Washington Generals, typicalGamePurpose, entertainment]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalGamePurpose Context triple: [Washington Generals, typicalGamePurpose, entertainment]
-
A.
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.
-
B.
isTypicallyPlayed
Indicates that an activity, game, or sport is commonly engaged in or performed by a particular type of participant or group.
-
C.
primaryUseDuringGames
Indicates that something is mainly used or employed during games or gameplay activities.
-
D.
typicallyPlays
Indicates that an entity is most commonly or habitually associated with playing a particular role, instrument, position, or type of game.
-
E.
primaryGameType
Indicates the main category or type of game with which an entity is primarily associated.
- 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_69f349dabc008190a18999c26682ed47 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c92f03c8190ae2751270b195423 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c80ba448190853011097a151b7e |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 1, 2026, 2:05 a.m.