Triple

T30907622
Position Surface form Disambiguated ID Type / Status
Subject Peren district E787345 entity
Predicate governingBody P46 FINISHED
Object District Administration of Peren
The District Administration of Peren is the local governmental authority responsible for overseeing civil administration, development programs, and public services in Nagaland’s Peren district.
E787345 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: District Administration of Peren | Statement: [Peren district, governingBody, District Administration of Peren]
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: District Administration of Peren
Triple: [Peren district, governingBody, District Administration of Peren]
Generated description
The District Administration of Peren is the local governmental authority responsible for overseeing civil administration, development programs, and public services in Nagaland’s Peren district.

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_69f224be300c8190a6513ce1ee0a7026 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69281097081908756e0720f537ba1 completed May 3, 2026, 12:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a28c7f3a56c8190886cd2a315359c89 completed June 10, 2026, 2:12 a.m.
NEDg Description generation batch_6a28cafd0fec8190b5977e2cf669c9fe completed June 10, 2026, 2:25 a.m.
NED2 Entity disambiguation (via description) batch_6a28cb7c04548190bdf6d0e5b55ebe45 completed June 10, 2026, 2:27 a.m.
Created at: April 29, 2026, 8:50 p.m.