Triple

T4429385
Position Surface form Disambiguated ID Type / Status
Subject Province of Cebu E95287 entity
Predicate hasMunicipality P847 FINISHED
Object Bogo
Bogo is a component city located in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding municipalities and islands.
 E440871 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: Bogo | Statement: [Province of Cebu, hasMunicipality, Bogo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bogo
Context triple: [Province of Cebu, hasMunicipality, Bogo]
  • A. Bogo
    Bogo is an alternative name for the Bilen people, an ethnic group primarily living in Eritrea.
  • B. Boebe
    Boebe was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources and associated with nearby Lake Boebeis.
  • C. Bosh
    Bosh is a surname most prominently associated with Chris Bosh, a retired American professional basketball player and two-time NBA champion.
  • D. Bube
    Bube is a Bantu language spoken primarily by the Bubi people on Bioko Island in Equatorial Guinea.
  • E. Boe
    Boe is a city in Guinea-Bissau known as the site where the Boé Declaration on Regional Security was adopted.
  • 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: Bogo
Triple: [Province of Cebu, hasMunicipality, Bogo]
Generated description
Bogo is a component city located in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding municipalities and islands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bogo
Target entity description: Bogo is a component city located in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding municipalities and islands.
  • A. Bogo
    Bogo is an alternative name for the Bilen people, an ethnic group primarily living in Eritrea.
  • B. Boebe
    Boebe was an ancient town in the region of Magnesia in Thessaly, Greece, known from classical sources and associated with nearby Lake Boebeis.
  • C. Bosh
    Bosh is a surname most prominently associated with Chris Bosh, a retired American professional basketball player and two-time NBA champion.
  • D. Bube
    Bube is a Bantu language spoken primarily by the Bubi people on Bioko Island in Equatorial Guinea.
  • E. Boe
    Boe is a city in Guinea-Bissau known as the site where the Boé Declaration on Regional Security was adopted.
  • 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_69b3453c2a0c8190926b574c90766db9 completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b35568767c819084d5e18b56a4745e completed March 13, 2026, 12:08 a.m.
NED1 Entity disambiguation (via context triple) batch_69b6136caa248190a84423cede1908c3 completed March 15, 2026, 2:03 a.m.
NEDg Description generation batch_69b617c13d4481909d22d201ce405d3a completed March 15, 2026, 2:21 a.m.
NED2 Entity disambiguation (via description) batch_69b6187687f8819084e2d611e9e31f79 completed March 15, 2026, 2:24 a.m.
Created at: March 12, 2026, 11:30 p.m.