Triple
T27925344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stanton Drew North-East Circle |
E707817
|
entity |
| Predicate | hasNumberOfSurvivingStones |
P19192
|
FINISHED |
| Object | 7 |
—
|
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: 7 | Statement: [Stanton Drew North-East Circle, hasNumberOfSurvivingStones, 7]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNumberOfSurvivingStones Context triple: [Stanton Drew North-East Circle, hasNumberOfSurvivingStones, 7]
-
A.
numberOfStones
chosen
Indicates the quantitative count of stones associated with a given entity or context.
-
B.
numberOfMajorStones
Indicates the quantity of major stones associated with or involved in a given entity or context.
-
C.
numberOfStoneRows
Indicates the count of distinct rows composed of stones associated with an entity.
-
D.
hasNumberOfSquares
Indicates that an entity is associated with a specific count of squares it contains or comprises.
-
E.
hasKomiRule
Indicates that a game or match is governed by a specific komi rule, defining the compensation points given to one player.
- 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_69ef96bbf2c48190a9d0e0291457aab6 |
completed | April 27, 2026, 5:02 p.m. |
| NER | Named-entity recognition | batch_69f7bbf906d8819099020e548dd56bc9 |
completed | May 3, 2026, 9:19 p.m. |
| PD | Predicate disambiguation | batch_69f7b9a2dcf88190a7c9e109e41267be |
completed | May 3, 2026, 9:09 p.m. |
Created at: April 27, 2026, 6:59 p.m.