Triple

T10223284
Position Surface form Disambiguated ID Type / Status
Subject Mancherial district E242635 entity
Predicate administrativeHeadquarters P62 FINISHED
Object Mancherial E850505 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: Mancherial | Statement: [Mancherial district, administrativeHeadquarters, Mancherial]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mancherial
Context triple: [Mancherial district, administrativeHeadquarters, Mancherial]
  • A. Mancherial chosen
    Mancherial is a town in the Indian state of Telangana known as a regional commercial and industrial center, particularly for coal mining and related industries.
  • B. Yelamanchili
    Yelamanchili is a town in the Visakhapatnam district of Andhra Pradesh, India, known for its historical significance and proximity to the Eastern Ghats.
  • C. Kadaru
    Kadaru is a Nubian language spoken by the Kadaru people in parts of Sudan.
  • D. Manpada
    Manpada is a residential suburb located in the city of Thane in the Mumbai Metropolitan Region of Maharashtra, India.
  • E. Tathra
    Tathra is a coastal town on the Sapphire Coast of New South Wales, Australia, known for its historic wharf, scenic beaches, and fishing.
  • 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_69d381ae26c48190985abd0e25ee5d04 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d3aa8305e481908ee1fc1d9eda6fa0 completed April 6, 2026, 12:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69d6f70a23288190a1dbb67324cfd799 completed April 9, 2026, 12:47 a.m.
Created at: April 6, 2026, 11:10 a.m.