Triple

T14452119
Position Surface form Disambiguated ID Type / Status
Subject Sirmour district E358362 entity
Predicate administrativeCentre P1474 FINISHED
Object Nahan E358363 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: Nahan | Statement: [Sirmour district, administrativeCentre, Nahan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Nahan
Context triple: [Sirmour district, administrativeCentre, Nahan]
  • A. Nahan chosen
    Nahan is a small hill town and municipal council in Himachal Pradesh, India, known for its scenic surroundings, pleasant climate, and role as a regional administrative and commercial center.
  • B. Ahan
    Ahan is a lesser-known Niger-Congo language spoken in parts of Nigeria, closely related to and geographically adjacent to Ukaan.
  • C. Nawalane
    Nawalane is a residential neighborhood located within the Lyari area of Karachi, Pakistan.
  • D. Nasib
    Nasib is a given name most notably borne by Nasib Yusifbeyli, an Azerbaijani statesman and political figure of the early 20th century.
  • E. Nawat
    Nawat is an indigenous Uto-Aztecan language of El Salvador, traditionally spoken by the Pipil people and now the focus of revitalization efforts.
  • 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_69d82794dfa081909b9134ad2e32244b completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de916244948190bb09d1bfc485ba50 completed April 14, 2026, 7:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd648f56608190b6d55c592c088575 completed May 8, 2026, 4:20 a.m.
Created at: April 10, 2026, 1:19 a.m.