Triple
T923805
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Constituent Assembly of India |
E19938
|
entity |
| Predicate | numberOfMembersAfterPartition |
P21589
|
FINISHED |
| Object | 299 |
—
|
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: 299 | Statement: [Constituent Assembly of India, numberOfMembersAfterPartition, 299]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfMembersAfterPartition Context triple: [Constituent Assembly of India, numberOfMembersAfterPartition, 299]
-
A.
numberOfKnownMembers
Indicates the count of members within a group or set whose identities are known or have been explicitly determined.
-
B.
originalNumberOfMembers
Indicates the initial total count of members in a group or organization before any changes such as additions or removals.
-
C.
numberOfFullMembers
Indicates the total count of entities that hold full membership status within a specified group or organization.
-
D.
numberOfNonPermanentMembers
Indicates the count of entities that hold non-permanent (temporary or rotating) membership within a larger group or body.
-
E.
numberOfParticipants
Indicates the total count of entities involved in a particular event, activity, or relationship.
- 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_69a493a099788190a696d9d8408cbaf4 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3296f50819087f809fbe90b139e |
completed | March 1, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69a4b295b02481908e5f53bfcb83cc94 |
completed | March 1, 2026, 9:41 p.m. |
| PDg | Predicate description generation | batch_69a4b30efd2c8190b780a6dee086d0aa |
completed | March 1, 2026, 9:43 p.m. |
Created at: March 1, 2026, 7:40 p.m.