Triple

T12375763
Position Surface form Disambiguated ID Type / Status
Subject Aurangabad, Bihar E295117 entity
Predicate hasNearbyUrbanCenters P36605 FINISHED
Object Gaya E295112 NE FINISHED

How this triple was built (3 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: Gaya | Statement: [Aurangabad, Bihar, hasNearbyUrbanCenters, Gaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gaya
Context triple: [Aurangabad, Bihar, hasNearbyUrbanCenters, Gaya]
  • A. Gaya chosen
    Gaya is a historic city in the Indian state of Bihar, renowned as a major Hindu and Buddhist pilgrimage center, especially for the Vishnupad Temple and its proximity to Bodh Gaya.
  • B. Gaya
    Gaya is a historic town and important urban center in northern Nigeria’s Kano State.
  • C. Giha
    Giha is an alternate name for the Ha language, a Bantu language spoken primarily in western Tanzania.
  • D. Geisa
    Geisa is a small historic town in the state of Thuringia in central Germany, near the former inner-German border.
  • E. Aisai
    Aisai is a city in central Japan known for its agricultural landscape and location within Aichi Prefecture near the Nagoya metropolitan area.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: hasNearbyUrbanCenters
Context triple: [Aurangabad, Bihar, hasNearbyUrbanCenters, Gaya]
  • A. nearbyUrbanCenter chosen
    Indicates that one location is geographically close to an urban center, such as a city or large town.
  • B. hasNearbyCityArea
    Indicates that one area is geographically close to or adjacent to a city area.
  • C. hasMunicipalitySeatNearby
    Indicates that the municipality’s administrative seat is located in close proximity to the referenced place or entity.
  • D. hasRegionalCenterNearby
    Indicates that a regional center is located in close proximity to the referenced entity.
  • E. connectsToUrbanCenter
    Indicates that one entity has a direct or functional linkage to an urban center, such as through infrastructure, services, or regular interaction.
  • F. None of above.

Provenance (4 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_69d6ab6d8a4081908636601e69ddf262 completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d93fb8d6c081909e8bbbd52c73f29c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f634760210819080bc0261aa059132 completed May 2, 2026, 5:29 p.m.
PD Predicate disambiguation batch_69d93ed256788190b704cad171a4824e completed April 10, 2026, 6:17 p.m.
Created at: April 8, 2026, 9:54 p.m.