Triple

T17581540
Position Surface form Disambiguated ID Type / Status
Subject Saharanpur district E428214 entity
Predicate hasTown P847 FINISHED
Object Gangoh
Gangoh is a town in the Saharanpur district of Uttar Pradesh, India, known for its historical and religious significance.
E1276378 NE FINISHED

How this triple was built (4 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: Gangoh | Statement: [Saharanpur district, hasTown, Gangoh]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gangoh
Context triple: [Saharanpur district, hasTown, Gangoh]
  • A. Ghangaria
    Ghangaria is a small Himalayan village in Uttarakhand, India, that serves as the base camp for pilgrims to Hemkunt Sahib and trekkers to the Valley of Flowers.
  • B. Ghoghardiha
    Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
  • C. Chamkoria
    Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
  • D. Ghatshila
    Ghatshila is a scenic town in Jharkhand, India, known for its forested hills, waterfalls, and literary association with Bengali writer Bibhutibhushan Bandyopadhyay.
  • E. Laxmangarh
    Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg Description generation gpt-5.1
Instruction
Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Gangoh
Triple: [Saharanpur district, hasTown, Gangoh]
Generated description
Gangoh is a town in the Saharanpur district of Uttar Pradesh, India, known for its historical and religious significance.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Gangoh
Target entity description: Gangoh is a town in the Saharanpur district of Uttar Pradesh, India, known for its historical and religious significance.
  • A. Ghangaria
    Ghangaria is a small Himalayan village in Uttarakhand, India, that serves as the base camp for pilgrims to Hemkunt Sahib and trekkers to the Valley of Flowers.
  • B. Ghoghardiha
    Ghoghardiha is a town located in the Madhubani district of the Indian state of Bihar.
  • C. Chamkoria
    Chamkoria is the former name of Borovets, one of Bulgaria’s oldest and most popular mountain ski resorts.
  • D. Ghatshila
    Ghatshila is a scenic town in Jharkhand, India, known for its forested hills, waterfalls, and literary association with Bengali writer Bibhutibhushan Bandyopadhyay.
  • E. Laxmangarh
    Laxmangarh is a town in the Sikar district of Rajasthan, India, known for its historic fort, havelis, and traditional Rajasthani architecture.
  • F. None of above. chosen

Provenance (5 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_69d889e1030481909950e140c63255b9 completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e463ce8eb081909257be47d150aa04 completed April 19, 2026, 5:10 a.m.
NED1 Entity disambiguation (via context triple) batch_6a01ddef82d48190a5940f7da646c380 completed May 11, 2026, 1:47 p.m.
NEDg Description generation batch_6a01de93c1448190aa2328919d407252 completed May 11, 2026, 1:50 p.m.
NED2 Entity disambiguation (via description) batch_6a01e05515d88190b343ebc1aad4a351 completed May 11, 2026, 1:57 p.m.
Created at: April 10, 2026, 5:50 a.m.