Triple
T4896294
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Greek cross |
E109687
|
entity |
| Predicate | hasRightAngleIntersections |
P60477
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Greek cross, hasRightAngleIntersections, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRightAngleIntersections Context triple: [Greek cross, hasRightAngleIntersections, true]
-
A.
hasCrossingPoint
Indicates that two or more entities intersect or share at least one common point in space or along their paths.
-
B.
isQuadrangleOf
Indicates that one entity is a four-sided polygon (quadrilateral) that has the other entity as its defining instance or member.
-
C.
hadCrossingPoints
Indicates that two entities intersected or overlapped at one or more specific points in space or time.
-
D.
hasNotableIntersection
Indicates that two entities intersect or cross at a point that is considered significant or noteworthy in some context.
-
E.
hasCorner
Indicates that one entity possesses or includes a corner that is part of or associated with another entity.
- 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_69bd4410bbf88190aad50d2451c863d6 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ffabccc81909115ece1b04e2061 |
completed | March 20, 2026, 4:04 p.m. |
| PD | Predicate disambiguation | batch_69bd6c2e7b5c8190b8bf9d616dfa24f0 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6ff731188190a9903602122d4ff9 |
completed | March 20, 2026, 4:04 p.m. |
Created at: March 20, 2026, 1:28 p.m.