Triple
T5362927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Scorpius–Centaurus OB association |
E103062
|
entity |
| Predicate | hasAngularExtent |
P20336
|
FINISHED |
| Object | over 100 degrees on the sky |
—
|
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: over 100 degrees on the sky | Statement: [Scorpius–Centaurus OB association, hasAngularExtent, over 100 degrees on the sky]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAngularExtent Context triple: [Scorpius–Centaurus OB association, hasAngularExtent, over 100 degrees on the sky]
-
A.
hasApproximateExtent
chosen
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
B.
hasDimension
Indicates that an entity possesses a specific measurable extent or size along one or more axes (e.g., length, width, height).
-
C.
hasWidth
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
D.
hasRightAngleIntersections
Indicates that the entities intersect each other at right (90-degree) angles.
-
E.
hasRange
Indicates that a property or relation is constrained to take its values from a specified class, type, or value set.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865b9b808190a1e8c283ba28d645 |
completed | March 20, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.