Triple
T25433515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Domineering |
E637317
|
entity |
| Predicate | hasBoardRepresentation |
P103
|
FINISHED |
| Object | grid of squares |
—
|
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: grid of squares | Statement: [Domineering, hasBoardRepresentation, grid of squares]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBoardRepresentation Context triple: [Domineering, hasBoardRepresentation, grid of squares]
-
A.
hasBoardComposition
Indicates that an entity has a specific structure or makeup of its governing board, such as the types or proportions of members who serve on it.
-
B.
hasBoardType
Indicates that an entity is associated with or uses a specific type or category of board.
-
C.
hasBoardSize
Indicates that an entity is associated with a board whose dimensions or overall size are specified.
-
D.
usesBoardShape
Indicates that one entity employs or is designed to work with a particular board shape as part of its function or configuration.
-
E.
hasRepresentationIn
chosen
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
- 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_69e75db6c97081908178383fa632b193 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f606c79ad081908369605f72e65ca6 |
completed | May 2, 2026, 2:14 p.m. |
| PD | Predicate disambiguation | batch_69f602ce79ec8190b8336c2b9de18ac7 |
completed | May 2, 2026, 1:57 p.m. |
Created at: April 21, 2026, 1:59 p.m.