Triple
T17951805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nakshatras |
E448848
|
entity |
| Predicate | alternativeNumberOfDivisions |
P1905
|
FINISHED |
| Object | 28 |
—
|
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: 28 | Statement: [Nakshatras, alternativeNumberOfDivisions, 28]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: alternativeNumberOfDivisions Context triple: [Nakshatras, alternativeNumberOfDivisions, 28]
-
A.
hasNumberOfDivisions
chosen
Indicates the relationship that specifies how many divisions or subunits an entity possesses.
-
B.
parallelDivision
Indicates that one entity is divided or partitioned in a way that runs parallel to the division or partitioning of another entity.
-
C.
divisionSize
Indicates the size or magnitude of a division or subdivided part in relation to a whole.
-
D.
divisionFrequency
Indicates how often a division event occurs within a given context or time frame.
-
E.
relatedDivide
Indicates that one entity divides or partitions another entity in a way that is contextually or relationally significant, rather than purely numerical.
- 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_69d8b9f8cca8819099836916c56b7c95 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e4afac95048190a5d1ef012899c62b |
completed | April 19, 2026, 10:34 a.m. |
| PD | Predicate disambiguation | batch_69e3f8f2bd088190b1e22ad4d9cc8b13 |
completed | April 18, 2026, 9:34 p.m. |
Created at: April 10, 2026, 10:21 a.m.