Triple

T20354269
Position Surface form Disambiguated ID Type / Status
Subject Kapan E496099 entity
Predicate formerName P65 FINISHED
Object Kafan
Kafan is a town in southern Armenia that serves as the administrative center of the Syunik Province and is known for its mining industry.
 E1425166 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: Kafan | Statement: [Kapan, formerName, Kafan]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kafan
Context triple: [Kapan, formerName, Kafan]
  • A. Taza
    Taza was a 19th-century Apache leader and the son of the famous chief Cochise, known for succeeding his father as a chief of the Chiricahua Apache.
  • B. Taza
    Taza is a historic city in northern Morocco known for its strategic location between the Rif and Middle Atlas mountains and its role as a key passage linking eastern and western Morocco.
  • C. Kupchino
    Kupchino is a residential district in the south of Saint Petersburg, Russia, known for its large Soviet-era housing estates and as a major transport hub.
  • D. Cafiero
    Cafiero is an Italian surname most notably associated with Carlo Cafiero, a prominent 19th-century anarchist and socialist activist.
  • E. Terqa
    Terqa was an ancient Mesopotamian city on the middle Euphrates, serving as a regional political and commercial center in what is now eastern Syria.
  • 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: Kafan
Triple: [Kapan, formerName, Kafan]
Generated description
Kafan is a town in southern Armenia that serves as the administrative center of the Syunik Province and is known for its mining industry.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kafan
Target entity description: Kafan is a town in southern Armenia that serves as the administrative center of the Syunik Province and is known for its mining industry.
  • A. Taza
    Taza was a 19th-century Apache leader and the son of the famous chief Cochise, known for succeeding his father as a chief of the Chiricahua Apache.
  • B. Taza
    Taza is a historic city in northern Morocco known for its strategic location between the Rif and Middle Atlas mountains and its role as a key passage linking eastern and western Morocco.
  • C. Kupchino
    Kupchino is a residential district in the south of Saint Petersburg, Russia, known for its large Soviet-era housing estates and as a major transport hub.
  • D. Cafiero
    Cafiero is an Italian surname most notably associated with Carlo Cafiero, a prominent 19th-century anarchist and socialist activist.
  • E. Terqa
    Terqa was an ancient Mesopotamian city on the middle Euphrates, serving as a regional political and commercial center in what is now eastern Syria.
  • 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_69e0b4a3f7f48190b37f354574028ca6 completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e67852ca9881908a5af18005639859 completed April 20, 2026, 7:02 p.m.
NED1 Entity disambiguation (via context triple) batch_6a086967aef88190b138be722f410e82 completed May 16, 2026, 12:56 p.m.
NEDg Description generation batch_6a0869f7b4208190858fdeae882e008d completed May 16, 2026, 12:58 p.m.
NED2 Entity disambiguation (via description) batch_6a086a893f1c81909bc40e3c4db0e147 completed May 16, 2026, 1 p.m.
Created at: April 16, 2026, 11:25 a.m.