Triple

T11455114
Position Surface form Disambiguated ID Type / Status
Subject Kohat District E271504 entity
Predicate hasSettlement P1068 FINISHED
Object Shakardara
Shakardara is a town and administrative settlement in Pakistan’s Khyber Pakhtunkhwa province, known for its role within the Kohat region.
E925610 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: Shakardara | Statement: [Kohat District, hasSettlement, Shakardara]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Shakardara
Context triple: [Kohat District, hasSettlement, Shakardara]
  • A. Shahdara
    Shahdara is a densely populated residential and commercial locality in East Delhi, India, known as one of the city’s oldest suburbs and a key transport hub.
  • B. Shekhan
    Shekhan is a town in northern Iraq that serves as one of the main cultural and residential centers of the Yazidi community.
  • C. Sakesar
    Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
  • D. Khar
    Khar is a suburban neighborhood in Mumbai, India, known for its residential areas, shopping streets, and proximity to the Arabian Sea.
  • E. Khar
    Khar is a town in northwestern Pakistan that serves as the administrative and commercial center of the Bajaur region in Khyber Pakhtunkhwa.
  • 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: Shakardara
Triple: [Kohat District, hasSettlement, Shakardara]
Generated description
Shakardara is a town and administrative settlement in Pakistan’s Khyber Pakhtunkhwa province, known for its role within the Kohat region.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Shakardara
Target entity description: Shakardara is a town and administrative settlement in Pakistan’s Khyber Pakhtunkhwa province, known for its role within the Kohat region.
  • A. Shahdara
    Shahdara is a densely populated residential and commercial locality in East Delhi, India, known as one of the city’s oldest suburbs and a key transport hub.
  • B. Shekhan
    Shekhan is a town in northern Iraq that serves as one of the main cultural and residential centers of the Yazidi community.
  • C. Sakesar
    Sakesar is a prominent mountain peak in Pakistan’s Punjab region, known for its scenic views, cooler climate, and strategic location within the Salt Range.
  • D. Khar
    Khar is a suburban neighborhood in Mumbai, India, known for its residential areas, shopping streets, and proximity to the Arabian Sea.
  • E. Khar
    Khar is a town in northwestern Pakistan that serves as the administrative and commercial center of the Bajaur region in Khyber Pakhtunkhwa.
  • 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_69d6aadff8888190a13f253f0d460874 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d81c7057688190ad8aa99426e4ca30 completed April 9, 2026, 9:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69e5d3e197c881909db2e4e59c61c3c3 completed April 20, 2026, 7:21 a.m.
NEDg Description generation batch_69e5d5cc251081908b85f264940a6545 completed April 20, 2026, 7:29 a.m.
NED2 Entity disambiguation (via description) batch_69e5d924963c8190bfc55ffeb529a499 completed April 20, 2026, 7:43 a.m.
Created at: April 8, 2026, 9:35 p.m.