Triple
T10489151
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Messier 30 |
E247367
|
entity |
| Predicate | OosterhoffType |
P94583
|
FINISHED |
| Object | II |
—
|
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: II | Statement: [Messier 30, OosterhoffType, II]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: OosterhoffType Context triple: [Messier 30, OosterhoffType, II]
-
A.
trumplerClassification
Indicates the classification of a star cluster according to the Trumpler system, describing its concentration, range of brightness, and richness.
-
B.
dominantSpectralType
Indicates the primary or most prevalent spectral type characterizing the electromagnetic emission of an object or region.
-
C.
isVariableStar
Indicates that an astronomical object exhibits intrinsic brightness variations over time, classifying it as a variable star.
-
D.
spectralClass
Indicates the classification of an astronomical object based on the characteristics of its spectrum, such as temperature and spectral features.
-
E.
astronomicalType
Indicates the classification relationship that specifies what kind of astronomical object or phenomenon something is (e.g., star, galaxy, planet).
- F. None of above. chosen
Provenance (4 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_69d381c309b88190af78aa681cf6a4c2 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5097ca5c081908b47a08ca7885650 |
completed | April 7, 2026, 1:41 p.m. |
| PD | Predicate disambiguation | batch_69d4fb8a30848190b33cf43f005a028e |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d5092af880819082b42c0a68e45c5f |
completed | April 7, 2026, 1:39 p.m. |
Created at: April 6, 2026, 12:23 p.m.