Triple

T10223283
Position Surface form Disambiguated ID Type / Status
Subject Mancherial district E242635 entity
Predicate hasHeadquarters P62 FINISHED
Object Mancherial
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.
E850505 NE FINISHED

How this triple was built (4 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, hasHeadquarters, Mancherial]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mancherial
Context triple: [Mancherial district, hasHeadquarters, Mancherial]
  • A. Yelamanchili
    Yelamanchili is a town in the Visakhapatnam district of Andhra Pradesh, India, known for its historical significance and proximity to the Eastern Ghats.
  • B. Kadaru
    Kadaru is a Nubian language spoken by the Kadaru people in parts of Sudan.
  • C. Manpada
    Manpada is a residential suburb located in the city of Thane in the Mumbai Metropolitan Region of Maharashtra, India.
  • D. Tathra
    Tathra is a coastal town on the Sapphire Coast of New South Wales, Australia, known for its historic wharf, scenic beaches, and fishing.
  • E. Mylavaram
    Mylavaram is a legislative assembly constituency in the Indian state of Andhra Pradesh that forms part of the Vijayawada Lok Sabha parliamentary seat.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Mancherial
Triple: [Mancherial district, hasHeadquarters, Mancherial]
Generated description
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.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Mancherial
Target entity description: 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.
  • A. Yelamanchili
    Yelamanchili is a town in the Visakhapatnam district of Andhra Pradesh, India, known for its historical significance and proximity to the Eastern Ghats.
  • B. Kadaru
    Kadaru is a Nubian language spoken by the Kadaru people in parts of Sudan.
  • C. Manpada
    Manpada is a residential suburb located in the city of Thane in the Mumbai Metropolitan Region of Maharashtra, India.
  • D. Tathra
    Tathra is a coastal town on the Sapphire Coast of New South Wales, Australia, known for its historic wharf, scenic beaches, and fishing.
  • E. Mylavaram
    Mylavaram is a legislative assembly constituency in the Indian state of Andhra Pradesh that forms part of the Vijayawada Lok Sabha parliamentary seat.
  • F. None of above. chosen

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_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_69d6a8457e9c819085f222bb002be892 completed April 8, 2026, 7:11 p.m.
NEDg Description generation batch_69d6d00220ec81909d189e64eda2a28f completed April 8, 2026, 10 p.m.
NED2 Entity disambiguation (via description) batch_69d6df44ad5481909100b596d2bf3b07 completed April 8, 2026, 11:05 p.m.
Created at: April 6, 2026, 11:10 a.m.