Triple
T869972
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seven Sisters |
E18787
|
entity |
| Predicate | hasAngularSize |
P6952
|
FINISHED |
| Object | about 110 arcminutes |
—
|
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: about 110 arcminutes | Statement: [Seven Sisters, hasAngularSize, about 110 arcminutes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAngularSize Context triple: [Seven Sisters, hasAngularSize, about 110 arcminutes]
-
A.
angularSize
chosen
Indicates the apparent size of an object as seen from a given point, typically measured as the angle it subtends at the observer.
-
B.
hasMeanRadius
Indicates that an entity possesses a specified average radius measurement, typically representing the mean distance from its center to its surface.
-
C.
hasFieldOfView
Indicates that one entity possesses a visual coverage area within which it can perceive or detect other entities or regions.
-
D.
hasDimensionsApprox
Indicates that an entity has physical dimensions that are known only approximately, rather than as exact measurements.
-
E.
hasRelativeSize
Indicates that one entity’s size is being compared to another entity’s size, expressing a relative rather than absolute magnitude.
- 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_69a4938ce8688190a24bdfef82ba7d21 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac811e548190a72b7a10b5ea8665 |
completed | March 1, 2026, 9:15 p.m. |
| PD | Predicate disambiguation | batch_69a4aa89ca008190b50d061ac7fe19f9 |
completed | March 1, 2026, 9:07 p.m. |
Created at: March 1, 2026, 7:39 p.m.