Triple

T10713049
Position Surface form Disambiguated ID Type / Status
Subject Nizamabad district E252588 entity
Predicate headquarters P62 FINISHED
Object Nizamabad E252588 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: Nizamabad | Statement: [Nizamabad district, headquarters, Nizamabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nizamabad
Context triple: [Nizamabad district, headquarters, Nizamabad]
  • A. Mahbubnagar
    Mahbubnagar is a town and district headquarters in the Indian state of Telangana, known for its agricultural surroundings and proximity to major rivers and irrigation projects.
  • B. Nizamabad district chosen
    Nizamabad district is an administrative region in the Indian state of Telangana, known for its agricultural economy, historical sites, and reliance on river-based irrigation.
  • C. Guntur
    Guntur is a major city in the Indian state of Andhra Pradesh, known historically as an important administrative and commercial center in southeastern India.
  • D. Guntur
    Guntur is a volcanic mountain in West Java, Indonesia, known for its geothermal activity and scenic hiking routes.
  • E. Kakinada
    Kakinada is a coastal city in the Indian state of Andhra Pradesh, known for its port, seafood industry, and role as a regional commercial hub.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69d6aa5cbabc8190973e683950d89faf completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d6fe54465081909640f6d7a2314fcb completed April 9, 2026, 1:18 a.m.
NED1 Entity disambiguation (via context triple) batch_69dbb70f67c88190980f362fcea9d800 completed April 12, 2026, 3:15 p.m.
Created at: April 8, 2026, 9:13 p.m.