Triple
T22077616
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seventh Schedule of the Constitution of India |
E545560
|
entity |
| Predicate | subjectCountNote |
P146556
|
FINISHED |
| Object | number of entries in each list has changed through constitutional amendments |
—
|
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: number of entries in each list has changed through constitutional amendments | Statement: [Seventh Schedule of the Constitution of India, subjectCountNote, number of entries in each list has changed through constitutional amendments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: subjectCountNote Context triple: [Seventh Schedule of the Constitution of India, subjectCountNote, number of entries in each list has changed through constitutional amendments]
-
A.
subjectCount
Indicates the number of subjects associated with or involved in a given entity or context.
-
B.
subjectNumber
Indicates the numerical identifier or count associated with the subject in the relationship.
-
C.
notableCount
Indicates the number of notable or distinguished items, entities, or instances associated with a given subject.
-
D.
hasSubjectCount
Indicates that an entity is associated with a specific number of subjects.
-
E.
disciplineCount
Indicates the number of disciplinary actions or incidents associated with an entity.
- 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_69e11e3523488190badd54b5d580c00d |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f128b38844819084526372fa6c6e35 |
completed | April 28, 2026, 9:37 p.m. |
| PD | Predicate disambiguation | batch_69e6f64a6a70819089d1a6c3a2384861 |
completed | April 21, 2026, 4 a.m. |
| PDg | Predicate description generation | batch_69e6fad59ef48190b62a2af636918a15 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:28 p.m.