Triple

T14277700
Position Surface form Disambiguated ID Type / Status
Subject Shamshabad E353956 entity
Predicate governingBody P46 FINISHED
Object Shamshabad Municipality E353956 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: Shamshabad Municipality | Statement: [Shamshabad, governingBody, Shamshabad Municipality]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shamshabad Municipality
Context triple: [Shamshabad, governingBody, Shamshabad Municipality]
  • A. Shamshabad chosen
    Shamshabad is a suburban area near Hyderabad in the Indian state of Telangana, known primarily for hosting the Rajiv Gandhi International Airport.
  • B. Al Shahaniya Municipality
    Al Shahaniya Municipality is an administrative region in western Qatar known for its desert landscapes, camel racing track, and growing residential and industrial developments.
  • C. Saddar Town
    Saddar Town is a central, densely populated urban area of Karachi known for its historic markets, colonial-era architecture, and major commercial and administrative centers.
  • D. Shahabad
    Shahabad is a town in Uttar Pradesh, India, situated within the administrative boundaries of Rampur district.
  • E. Buraydah Municipality
    Buraydah Municipality is the local government authority responsible for urban planning, public services, and municipal administration in the city of Buraydah, Saudi Arabia.
  • 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_69d8278d25148190abf1a8c8f5f533ad completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de6583f0ec81909ebfc7a2c6351ff8 completed April 14, 2026, 4:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd326f62b4819084b1e984678991ae completed May 8, 2026, 12:46 a.m.
Created at: April 10, 2026, 1:10 a.m.