Triple
T26199426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | National Register of Citizens in Assam |
E655191
|
entity |
| Predicate | legalBasis |
P125
|
FINISHED |
| Object |
Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003
The Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003 are Indian government regulations that lay down the procedures for preparing and maintaining citizen registers and issuing national identity cards, forming the legal framework for exercises such as the National Register of Citizens.
|
E1716143
|
NE 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: Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003 | Statement: [National Register of Citizens in Assam, legalBasis, Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003]
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003 Triple: [National Register of Citizens in Assam, legalBasis, Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003]
Generated description
The Citizenship (Registration of Citizens and Issue of National Identity Cards) Rules, 2003 are Indian government regulations that lay down the procedures for preparing and maintaining citizen registers and issuing national identity cards, forming the legal framework for exercises such as the National Register of Citizens.
Provenance (5 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_69ee5b48236c81908fe385b6afc4f60b |
completed | April 26, 2026, 6:36 p.m. |
| NER | Named-entity recognition | batch_69f60cd9e50481908d1559e6ec048bc1 |
completed | May 2, 2026, 2:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a1185822d388190b3a272f8edf4acb9 |
completed | May 23, 2026, 10:46 a.m. |
| NEDg | Description generation | batch_6a1187b8aea88190b6ec7b999d2b37eb |
completed | May 23, 2026, 10:55 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a1188a2ea6081909e575aff107859ab |
completed | May 23, 2026, 10:59 a.m. |
Created at: April 26, 2026, 8:47 p.m.