Triple

T7236705
Position Surface form Disambiguated ID Type / Status
Subject Ramakrishnapur E155246 entity
Predicate hasName P744 FINISHED
Object Ramakrishnapur E155246 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: Ramakrishnapur | Statement: [Ramakrishnapur, hasName, Ramakrishnapur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Ramakrishnapur
Context triple: [Ramakrishnapur, hasName, Ramakrishnapur]
  • A. Ramakrishnapur chosen
    Ramakrishnapur is a village located on Little Andaman Island in the Andaman and Nicobar Islands of India.
  • B. Krishnanagar
    Krishnanagar is a historic town in eastern India known for its cultural heritage, temples, and traditional clay artistry.
  • C. Dharmanagar
    Dharmanagar is a prominent town and municipal council in the North Tripura district of the Indian state of Tripura, serving as an important local commercial and administrative center.
  • D. Babatpur
    Babatpur is a locality near Varanasi in the Indian state of Uttar Pradesh, known primarily for hosting the city’s main airport.
  • E. Kamalpur
    Kamalpur is a town in the northeastern Indian state of Tripura, known as a local administrative and commercial center in the region.
  • 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_69c688143bfc81908d4176617735e601 completed March 27, 2026, 1:37 p.m.
NER Named-entity recognition batch_69c6ea355e888190a97de097158933ca completed March 27, 2026, 8:36 p.m.
NED1 Entity disambiguation (via context triple) batch_69c7cc32d6c48190ae78b3d1227bb868 completed March 28, 2026, 12:40 p.m.
Created at: March 27, 2026, 2:55 p.m.