Triple

T10380756
Position Surface form Disambiguated ID Type / Status
Subject Hamedan Province E244633 entity
Predicate hasCity P316 FINISHED
Object Kabudarahang
Kabudarahang is a city in western Iran that serves as a local administrative and population center within Hamedan Province.
E859458 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: Kabudarahang | Statement: [Hamedan Province, hasCity, Kabudarahang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kabudarahang
Context triple: [Hamedan Province, hasCity, Kabudarahang]
  • A. Kulata
    Kulata is a village in southwestern Bulgaria near the Greek border, serving as an important border crossing and transport hub between the two countries.
  • B. Kaharingan
    Kaharingan is an indigenous animist and ancestor-venerating belief system of the Dayak peoples of Borneo, centered on harmony with nature and complex ritual practices.
  • C. Dadiangas
    Dadiangas is the former name of General Santos, a major city in the southern Philippines known for its tuna fishing industry.
  • D. Kabiye
    Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
  • E. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • 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: Kabudarahang
Triple: [Hamedan Province, hasCity, Kabudarahang]
Generated description
Kabudarahang is a city in western Iran that serves as a local administrative and population center within Hamedan Province.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kabudarahang
Target entity description: Kabudarahang is a city in western Iran that serves as a local administrative and population center within Hamedan Province.
  • A. Kulata
    Kulata is a village in southwestern Bulgaria near the Greek border, serving as an important border crossing and transport hub between the two countries.
  • B. Kaharingan
    Kaharingan is an indigenous animist and ancestor-venerating belief system of the Dayak peoples of Borneo, centered on harmony with nature and complex ritual practices.
  • C. Dadiangas
    Dadiangas is the former name of General Santos, a major city in the southern Philippines known for its tuna fishing industry.
  • D. Kabiye
    Kabiye is a Gur language spoken primarily in northern Togo and recognized as one of the country's major national languages.
  • E. Kalamansig
    Kalamansig is a coastal municipality in the province of Sultan Kudarat in the Philippines, known for its fishing industry and diverse indigenous communities.
  • 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_69d381b3e328819094b23b8edcd29b5a completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d4e9921fa48190a874aa9a9e385b97 completed April 7, 2026, 11:25 a.m.
NED1 Entity disambiguation (via context triple) batch_69d7958803e88190a7bbeda4f2c6f32c completed April 9, 2026, 12:03 p.m.
NEDg Description generation batch_69d79784baa481909e57adda27578cc2 completed April 9, 2026, 12:11 p.m.
NED2 Entity disambiguation (via description) batch_69d7989f8dfc8190b1fe4429f7bb0283 completed April 9, 2026, 12:16 p.m.
Created at: April 6, 2026, 12:03 p.m.