Triple
T6287040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Galactic thin disk |
E140925
|
entity |
| Predicate | hasApproximateRadialExtent |
P20336
|
FINISHED |
| Object | about 15 kiloparsecs |
—
|
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 15 kiloparsecs | Statement: [Galactic thin disk, hasApproximateRadialExtent, about 15 kiloparsecs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasApproximateRadialExtent Context triple: [Galactic thin disk, hasApproximateRadialExtent, about 15 kiloparsecs]
-
A.
radialExtent
Indicates the radial distance or range over which something extends outward from a central point or axis.
-
B.
hasApproximateExtent
chosen
Indicates that one entity has a spatial, temporal, or quantitative extent that is only roughly or approximately specified rather than exact.
-
C.
approximateRadius
Indicates that one entity specifies or provides an estimated value for the radius of another entity.
-
D.
hasApproximateShape
Indicates that one entity has a shape that is similar to, but not exactly the same as, the shape of another entity.
-
E.
hasOuterBoundaryRadius
Indicates that an entity has an outer boundary characterized by a specific radius measurement.
- 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_69c008cd17c8819082b82d3fbeb68047 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c063ff9f74819088dc603f56fc930c |
completed | March 22, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69c0560a0270819098ad2785b91e8f39 |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:26 p.m.