Triple
T11649932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aubrey holes |
E276874
|
entity |
| Predicate | formsCircleOf |
P88528
|
FINISHED |
| Object | approximately 86 metres in diameter |
—
|
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: approximately 86 metres in diameter | Statement: [Aubrey holes, formsCircleOf, approximately 86 metres in diameter]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: formsCircleOf Context triple: [Aubrey holes, formsCircleOf, approximately 86 metres in diameter]
-
A.
circleType
Indicates the specific classification or category of a circle within a given context or system.
-
B.
hasCircle
chosen
Indicates that one entity possesses, contains, or includes a circle as part of its structure or composition.
-
C.
circles
Indicates that one entity moves around another entity along a roughly circular path or orbit.
-
D.
formsAround
Indicates that one entity develops or shapes itself so as to encircle, surround, or be organized around another entity.
-
E.
formsGreatCircleWith
Indicates that two paths or segments together lie on the same great circle, forming a continuous great-circle route on a sphere.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a2cea9308190a13f7dd995ea07a4 |
completed | April 10, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69d85ddc780481909a3bc63832fe2bd2 |
completed | April 10, 2026, 2:18 a.m. |
Created at: April 8, 2026, 9:39 p.m.