Triple

T21709966
Position Surface form Disambiguated ID Type / Status
Subject Mathura–Kasganj line E535875 entity
Predicate connects P390 FINISHED
Object Kasganj 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: Kasganj | Statement: [Mathura–Kasganj line, connects, Kasganj]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kasganj
Context triple: [Mathura–Kasganj line, connects, Kasganj]
  • A. Kasganj chosen
    Kasganj is a town and district headquarters in the Indian state of Uttar Pradesh, known for its agricultural trade and regional connectivity.
  • B. Farashganj
    Farashganj is a historic neighborhood in Old Dhaka, Bangladesh, known for its colonial-era architecture and once-thriving merchant community.
  • C. Karauli
    Karauli is a historic town and pilgrimage center in the Indian state of Rajasthan, known for its ancient temples and distinctive red sandstone architecture.
  • D. Hoshangabad
    Hoshangabad is a city in the Indian state of Madhya Pradesh, known for its location on the banks of the Narmada River and its agricultural and industrial activities.
  • E. Narsinghgarh
    Narsinghgarh is a historic town in central India that once served as the administrative and cultural center of the former princely Narsinghgarh State.
  • 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_69e0c46b44c0819088ab883ebd44e0e8 completed April 16, 2026, 11:13 a.m.
NER Named-entity recognition batch_69efb5321d34819091f3cd03f7b407c0 completed April 27, 2026, 7:12 p.m.
Created at: April 16, 2026, 6:46 p.m.