Triple

T6083199
Position Surface form Disambiguated ID Type / Status
Subject Wardak Province E135572 entity
Predicate capital P234 FINISHED
Object Maidan Shahr
Maidan Shahr is a town in central Afghanistan that serves as the administrative and commercial hub of Wardak Province.
E566702 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: Maidan Shahr | Statement: [Wardak Province, capital, Maidan Shahr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maidan Shahr
Context triple: [Wardak Province, capital, Maidan Shahr]
  • A. Alma-Atinskaya
    Alma-Atinskaya is a southern terminus station of the Moscow Metro, serving as one endpoint of the Zamoskvoretskaya Line.
  • B. Azimabad
    Azimabad is the former Mughal-era name of the Indian city now known as Patna, reflecting its historical significance under imperial rule.
  • C. Karshi
    Karshi is a city in southern Uzbekistan known as an important regional center for industry, agriculture, and transportation.
  • D. Taşkent
    Taşkent is a small mountainous district and town in Turkey’s Konya Province, known for its rural character and scenic Anatolian landscape.
  • E. Andijan
    Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
  • 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: Maidan Shahr
Triple: [Wardak Province, capital, Maidan Shahr]
Generated description
Maidan Shahr is a town in central Afghanistan that serves as the administrative and commercial hub of Wardak Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Maidan Shahr
Target entity description: Maidan Shahr is a town in central Afghanistan that serves as the administrative and commercial hub of Wardak Province.
  • A. Alma-Atinskaya
    Alma-Atinskaya is a southern terminus station of the Moscow Metro, serving as one endpoint of the Zamoskvoretskaya Line.
  • B. Azimabad
    Azimabad is the former Mughal-era name of the Indian city now known as Patna, reflecting its historical significance under imperial rule.
  • C. Karshi
    Karshi is a city in southern Uzbekistan known as an important regional center for industry, agriculture, and transportation.
  • D. Taşkent
    Taşkent is a small mountainous district and town in Turkey’s Konya Province, known for its rural character and scenic Anatolian landscape.
  • E. Andijan
    Andijan is a historic city in eastern Uzbekistan, known as a major cultural and economic center of the Fergana Valley and as the birthplace of the Mughal emperor Babur.
  • 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_69c0087ad31c8190ab936e0ff28614b6 completed March 22, 2026, 3:19 p.m.
NER Named-entity recognition batch_69c05786233c81909010a6c2f7e7dfda completed March 22, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_69c11d57b5f481908d7df374837a486a completed March 23, 2026, 11 a.m.
NEDg Description generation batch_69c11e89c75481908381df126a7b1661 completed March 23, 2026, 11:05 a.m.
NED2 Entity disambiguation (via description) batch_69c11ef6971c8190b8dde5568b330b41 completed March 23, 2026, 11:07 a.m.
Created at: March 22, 2026, 4:11 p.m.