Triple
T11242748
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Conway's thrackle conjecture |
E266111
|
entity |
| Predicate | edgeIntersectionCondition |
P50696
|
FINISHED |
| Object | every pair of edges meets exactly once |
—
|
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: every pair of edges meets exactly once | Statement: [Conway's thrackle conjecture, edgeIntersectionCondition, every pair of edges meets exactly once]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: edgeIntersectionCondition Context triple: [Conway's thrackle conjecture, edgeIntersectionCondition, every pair of edges meets exactly once]
-
A.
fieldIntersection
Indicates that two or more fields or domains share a common overlapping area or set of elements.
-
B.
intersectionRole
Indicates a role or function that an entity specifically holds at the point where two or more entities, paths, or sets intersect.
-
C.
boardIntersectionCount
Indicates the number of distinct points or areas where two or more boards intersect or overlap.
-
D.
hasCrossingPoint
chosen
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
E.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
- 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_69d6aac656d48190b275efaa7d6074ee |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e91b0b808190bc38008bb344d180 |
completed | April 9, 2026, 5:59 p.m. |
| PD | Predicate disambiguation | batch_69d7878906f48190b63ddc103a0c8f9b |
completed | April 9, 2026, 11:03 a.m. |
Created at: April 8, 2026, 9:30 p.m.