Triple
T19686325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ptolemy Cluster |
E472719
|
entity |
| Predicate | approximateNumberOfStars |
P7300
|
FINISHED |
| Object | 80 |
—
|
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: 80 | Statement: [Ptolemy Cluster, approximateNumberOfStars, 80]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateNumberOfStars Context triple: [Ptolemy Cluster, approximateNumberOfStars, 80]
-
A.
approximateStellarCount
chosen
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
-
B.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
-
C.
approximateNumberOfGalaxies
Indicates an estimated or roughly calculated count of galaxies associated with a given subject.
-
D.
starCountSymbolizes
Indicates that the number of stars associated with something serves as a symbolic representation of a particular quality, status, or attribute.
-
E.
numberOfStarsInConstellation
Indicates the numerical count of stars that belong to a given constellation.
- 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_69d8e515bef88190bc30781aea50537a |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e6420c3f50819082b64b1fa4335e56 |
completed | April 20, 2026, 3:11 p.m. |
| PD | Predicate disambiguation | batch_69e53039ea808190a9106a53f564ab92 |
completed | April 19, 2026, 7:42 p.m. |
Created at: April 10, 2026, 1:45 p.m.