Triple
T11876327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blunder Bowl |
E282535
|
entity |
| Predicate | associatedWithGameNumber |
P102007
|
FINISHED |
| Object | V |
—
|
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: V | Statement: [Blunder Bowl, associatedWithGameNumber, V]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithGameNumber Context triple: [Blunder Bowl, associatedWithGameNumber, V]
-
A.
associatedWithGame
Indicates that there is a relationship or connection between an entity and a particular game.
-
B.
associatedWithPlayers
Indicates a relationship in which one or more players are connected, linked, or otherwise involved with the referenced entity.
-
C.
relatedGame
Indicates that one game has a notable connection or association with another game, such as shared content, themes, or series.
-
D.
associatedWithRivalryGame
Indicates that there is a connection or involvement between entities specifically in the context of a rivalry game.
-
E.
hasGamesAt
Indicates that a particular location, venue, or platform hosts or offers one or more games.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
| PDg | Predicate description generation | batch_69d8d399d58c81908dab572aa82426d7 |
completed | April 10, 2026, 10:40 a.m. |
Created at: April 8, 2026, 9:44 p.m.