Triple

T14127421
Position Surface form Disambiguated ID Type / Status
Subject Isfahan region E340068 entity
Predicate hasUrbanCenter P2106 FINISHED
Object Najafabad
Najafabad is a city in central Iran known as one of the major urban centers of Isfahan Province, with a strong agricultural base and growing industrial and educational sectors.
E1081383 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: Najafabad | Statement: [Isfahan region, hasUrbanCenter, Najafabad]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Najafabad
Context triple: [Isfahan region, hasUrbanCenter, Najafabad]
  • A. Sharifabad
    Sharifabad is a town located in Pakdasht County within Tehran Province in Iran.
  • B. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • C. Nasirabad
    Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
  • D. Salehabad
    Salehabad is a settlement located within Robat Karim County in Tehran Province, Iran.
  • E. Salehabad
    Salehabad is a village-level settlement located within Baharestan County in Tehran Province, Iran.
  • 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: Najafabad
Triple: [Isfahan region, hasUrbanCenter, Najafabad]
Generated description
Najafabad is a city in central Iran known as one of the major urban centers of Isfahan Province, with a strong agricultural base and growing industrial and educational sectors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Najafabad
Target entity description: Najafabad is a city in central Iran known as one of the major urban centers of Isfahan Province, with a strong agricultural base and growing industrial and educational sectors.
  • A. Sharifabad
    Sharifabad is a town located in Pakdasht County within Tehran Province in Iran.
  • B. Nasirabad
    Nasirabad is a town and administrative area located in the Balochistan region of present-day Pakistan.
  • C. Nasirabad
    Nasirabad is a village in the Lower Hunza region of northern Pakistan, known for its mountainous terrain and proximity to the Karakoram Range.
  • D. Salehabad
    Salehabad is a settlement located within Robat Karim County in Tehran Province, Iran.
  • E. Salehabad
    Salehabad is a village-level settlement located within Baharestan County in Tehran Province, Iran.
  • 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_69d81c6a95b481909e39111e0c1f31ee completed April 9, 2026, 9:38 p.m.
NER Named-entity recognition batch_69de6098013c8190b1bac9d3fff60acd completed April 14, 2026, 3:43 p.m.
NED1 Entity disambiguation (via context triple) batch_69fcdf0c833081908458e4eaee689df7 completed May 7, 2026, 6:50 p.m.
NEDg Description generation batch_69fce094bf3081909f7c0097dcb63398 completed May 7, 2026, 6:57 p.m.
NED2 Entity disambiguation (via description) batch_69fce14ff8e48190b3b663d130d18418 completed May 7, 2026, 7 p.m.
Created at: April 9, 2026, 10:22 p.m.