Triple

T14512368
Position Surface form Disambiguated ID Type / Status
Subject Batman Province E340428 entity
Predicate hasCity P316 FINISHED
Object Beşiri
Beşiri is a town and district in southeastern Turkey known for its predominantly Kurdish population and location within Batman Province.
E1102722 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: Beşiri | Statement: [Batman Province, hasCity, Beşiri]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Beşiri
Context triple: [Batman Province, hasCity, Beşiri]
  • A. Birsay
    Birsay is a coastal parish and village area on the northwest of Orkney Mainland in Scotland, known for its rich Norse history and archaeological sites.
  • B. Bisha
    Bisha is a major inland city in southwestern Saudi Arabia known for its agricultural production and strategic location within the Asir region.
  • C. Busia
    Busia is a Ghanaian surname most prominently associated with Kofi Abrefa Busia, a former Prime Minister of Ghana and influential political leader.
  • D. Busia
    Busia is a prominent border town in eastern Uganda that serves as a major commercial and transit hub between Uganda and Kenya.
  • E. Kasibu
    Kasibu is a rural municipality in the province of Nueva Vizcaya in the Philippines, known for its mountainous terrain and agricultural economy.
  • 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: Beşiri
Triple: [Batman Province, hasCity, Beşiri]
Generated description
Beşiri is a town and district in southeastern Turkey known for its predominantly Kurdish population and location within Batman Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Beşiri
Target entity description: Beşiri is a town and district in southeastern Turkey known for its predominantly Kurdish population and location within Batman Province.
  • A. Birsay
    Birsay is a coastal parish and village area on the northwest of Orkney Mainland in Scotland, known for its rich Norse history and archaeological sites.
  • B. Bisha
    Bisha is a major inland city in southwestern Saudi Arabia known for its agricultural production and strategic location within the Asir region.
  • C. Busia
    Busia is a Ghanaian surname most prominently associated with Kofi Abrefa Busia, a former Prime Minister of Ghana and influential political leader.
  • D. Busia
    Busia is a prominent border town in eastern Uganda that serves as a major commercial and transit hub between Uganda and Kenya.
  • E. Kasibu
    Kasibu is a rural municipality in the province of Nueva Vizcaya in the Philippines, known for its mountainous terrain and agricultural economy.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de9a6c6054819086b4c0ce1d83fdc5 completed April 14, 2026, 7:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da48b2c8190a906965a7ebcb607 completed May 8, 2026, 4:59 a.m.
NEDg Description generation batch_69fd6f94fd608190bf874869ff15fdf5 completed May 8, 2026, 5:07 a.m.
NED2 Entity disambiguation (via description) batch_69fd7041102c8190bc6f3d3011004d7a completed May 8, 2026, 5:10 a.m.
Created at: April 10, 2026, 1:21 a.m.