Triple

T13452915
Position Surface form Disambiguated ID Type / Status
Subject Samastipur E311154 entity
Predicate hasRailConnectivityTo P58937 FINISHED
Object Gorakhpur E94443 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: Gorakhpur | Statement: [Samastipur, hasRailConnectivityTo, Gorakhpur]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gorakhpur
Context triple: [Samastipur, hasRailConnectivityTo, Gorakhpur]
  • A. Gorakhpur chosen
    Gorakhpur is a prominent city in northern India known as a regional commercial, transportation, and cultural hub near the border with Nepal.
  • B. Kashipur
    Kashipur is a town in the Udham Singh Nagar district of Uttarakhand, India, known as an important industrial and commercial center in the region.
  • C. Kishanganj
    Kishanganj is a town and district headquarters in the northeastern part of the Indian state of Bihar, known for its significant Muslim population and proximity to the borders of West Bengal and Nepal.
  • D. Bhagalpur
    Bhagalpur is a historic city in the eastern Indian state of Bihar, known for its silk industry and location along the Ganges River.
  • E. Hajipur
    Hajipur is a prominent city in the Indian state of Bihar, known as an important railway and commercial hub located near the state capital, Patna.
  • 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_69d806a938b8819097ec43a2229fc7f9 completed April 9, 2026, 8:06 p.m.
NER Named-entity recognition batch_69dbaefae85481909e6a59797cbb25e7 completed April 12, 2026, 2:40 p.m.
NED1 Entity disambiguation (via context triple) batch_69f7b05a6d808190bae503b177816718 completed May 3, 2026, 8:30 p.m.
Created at: April 9, 2026, 9:41 p.m.