Triple
T21523281
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | M35 |
E531028
|
entity |
| Predicate | containsHundredsOfStars |
P7300
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [M35, containsHundredsOfStars, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsHundredsOfStars Context triple: [M35, containsHundredsOfStars, true]
-
A.
numberOfCentralStars
Indicates the quantity of central stars associated with or contained within a given entity or system.
-
B.
hasStars
Indicates that an entity possesses or is associated with one or more stars.
-
C.
approximateStellarCount
chosen
Indicates an estimated or rough number of stars associated with a given astronomical object or region.
-
D.
developedManyStars
Indicates that the subject played a significant role in nurturing, training, or promoting a large number of individuals who later became prominent or highly successful.
-
E.
starCount
Indicates the number of stars associated with an entity, typically representing a rating, quality level, or count of starred items.
- 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_69e0c45d95a081908e7962ad215da746 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69ee884db3ac81909e77d22d607ac72d |
completed | April 26, 2026, 9:49 p.m. |
| PD | Predicate disambiguation | batch_69e6320043bc81909417c41a718652ba |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:26 p.m.