Triple

T9950201
Position Surface form Disambiguated ID Type / Status
Subject Palamoor E195309 entity
Predicate refersTo P37 FINISHED
Object Mahbubnagar town E37569 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: Mahbubnagar town | Statement: [Palamoor, refersTo, Mahbubnagar town]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mahbubnagar town
Context triple: [Palamoor, refersTo, Mahbubnagar town]
  • A. Mahbubnagar chosen
    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. Bhimnagar
    Bhimnagar is a settlement in the Indian state of Bihar known for its proximity to the Kosi River and the major Kosi Barrage infrastructure.
  • C. Kondapur
    Kondapur is a rapidly developing residential and commercial suburb in Hyderabad, India, known for its proximity to major IT hubs and tech parks.
  • D. Nandyal
    Nandyal is a city in the Indian state of Andhra Pradesh, known as a commercial and administrative center in the Rayalaseema region.
  • E. Jangaon
    Jangaon is a town and municipal center in the Indian state of Telangana, known for its location along key road and rail routes between Hyderabad and Warangal.
  • 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_69ca82e96a108190932bd1fc4acd73a0 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cdb65a4e6c8190968192a24aad1b7d completed April 2, 2026, 12:20 a.m.
NED1 Entity disambiguation (via context triple) batch_69d257a164308190b88432b914ea7f1a completed April 5, 2026, 12:37 p.m.
Created at: March 30, 2026, 8:45 p.m.