Triple

T7753888
Position Surface form Disambiguated ID Type / Status
Subject Sibi District E175840 entity
Predicate contains P35 FINISHED
Object Harnai
Harnai is a town in Pakistan’s Balochistan province known for its coal mining and mountainous terrain.
 E685514 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: Harnai | Statement: [Sibi District, contains, Harnai]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Harnai
Context triple: [Sibi District, contains, Harnai]
  • A. Halisahar
    Halisahar is a town in the North 24 Parganas district of the Indian state of West Bengal, situated along the Hooghly River and forming part of the Kolkata metropolitan area.
  • B. Bhabra
    Bhabra is a town in the Alirajpur district of Madhya Pradesh, India, known as the birthplace of Indian revolutionary Chandra Shekhar Azad.
  • C. Kharp
    Kharp is a remote settlement in Russia’s Yamalo-Nenets Autonomous Okrug, known for hosting the high-security IK-3 “Polar Wolf” penal colony.
  • D. Harlakhi
    Harlakhi is a town in the Madhubani district of Bihar, India, known for its proximity to the India–Nepal border and its association with the Mithila region.
  • E. Bhailsa
    Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
  • 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: Harnai
Triple: [Sibi District, contains, Harnai]
Generated description
Harnai is a town in Pakistan’s Balochistan province known for its coal mining and mountainous terrain.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Harnai
Target entity description: Harnai is a town in Pakistan’s Balochistan province known for its coal mining and mountainous terrain.
  • A. Halisahar
    Halisahar is a town in the North 24 Parganas district of the Indian state of West Bengal, situated along the Hooghly River and forming part of the Kolkata metropolitan area.
  • B. Bhabra
    Bhabra is a town in the Alirajpur district of Madhya Pradesh, India, known as the birthplace of Indian revolutionary Chandra Shekhar Azad.
  • C. Kharp
    Kharp is a remote settlement in Russia’s Yamalo-Nenets Autonomous Okrug, known for hosting the high-security IK-3 “Polar Wolf” penal colony.
  • D. Harlakhi
    Harlakhi is a town in the Madhubani district of Bihar, India, known for its proximity to the India–Nepal border and its association with the Mithila region.
  • E. Bhailsa
    Bhailsa is the former historical name of Vidisha, an ancient city in the central Indian state of Madhya Pradesh known for its rich archaeological and cultural heritage.
  • 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_69c6996180088190832e38e8d83ff54a completed March 27, 2026, 2:51 p.m.
NER Named-entity recognition batch_69c703d851d4819091e9117d3f34cb9a completed March 27, 2026, 10:25 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8be5a649c81909c94d629348b34fc completed March 29, 2026, 5:53 a.m.
NEDg Description generation batch_69c8bf06242c8190b38bae041484096d completed March 29, 2026, 5:56 a.m.
NED2 Entity disambiguation (via description) batch_69c8bf5aa1348190a5c369bece6fb6db completed March 29, 2026, 5:57 a.m.
Created at: March 27, 2026, 4:08 p.m.