Triple
T8482424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Go |
E200551
|
entity |
| Predicate | boardIntersectionCount |
P82854
|
FINISHED |
| Object | 361 on 19x19 board |
—
|
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: 361 on 19x19 board | Statement: [Go, boardIntersectionCount, 361 on 19x19 board]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: boardIntersectionCount Context triple: [Go, boardIntersectionCount, 361 on 19x19 board]
-
A.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
-
B.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
C.
crossesBetween
Indicates that one entity passes from one side of a second entity to the other, traversing the space between two reference points or boundaries associated with that second entity.
-
D.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
E.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
- 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_69ca831b17988190a1f3f3413d57b820 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe53638c48190b742fc51d1b4442a |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd104250c8190b4c499dcc9937494 |
completed | March 31, 2026, 1:49 p.m. |
| PDg | Predicate description generation | batch_69cbe12dd0b88190a38ec4d15dcc870b |
completed | March 31, 2026, 2:58 p.m. |
Created at: March 30, 2026, 6:12 p.m.