Triple

T19922505
Position Surface form Disambiguated ID Type / Status
Subject Datia railway station E478832 entity
Predicate serves P98 FINISHED
Object Datia city NE NERFINISHED

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: Datia city | Statement: [Datia railway station, serves, Datia city]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Datia city
Context triple: [Datia railway station, serves, Datia city]
  • A. Datia town chosen
    Datia town is a historic urban center in Madhya Pradesh, India, known for its hilltop palaces, temples, and rich Bundelkhand architectural heritage.
  • B. Satna city
    Satna city is an urban center in the Indian state of Madhya Pradesh, known as a regional commercial and transportation hub.
  • C. Dhar
    Dhar is a historic town and administrative center in the Indian state of Madhya Pradesh, known for its medieval forts, Islamic architecture, and cultural heritage.
  • D. Betul city
    Betul city is an urban center in the Betul district of Madhya Pradesh, India, known as a regional hub for trade, agriculture, and transportation.
  • E. City of Sagar
    The City of Sagar is an urban center in the Indian state of Madhya Pradesh, known for its administrative importance, educational institutions, and cultural heritage.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69d8e521855c8190b41871700afc8d6a completed April 10, 2026, 11:55 a.m.
NER Named-entity recognition batch_69e659c6919c8190a96106532580b6b6 completed April 20, 2026, 4:52 p.m.
Created at: April 10, 2026, 1:53 p.m.