Triple

T2375878
Position Surface form Disambiguated ID Type / Status
Subject Cebu E46197 entity
Predicate hasPart P35 FINISHED
Object Bogo City
Bogo City is a component city in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding rural municipalities.
 E261527 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 City | Statement: [Cebu, hasPart, Bogo City]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Bogo City
Context triple: [Cebu, hasPart, Bogo City]
  • A. South City
    South City is a colloquial name for South San Francisco, a suburban city in San Mateo County, California, known for its industrial history and proximity to San Francisco.
  • B. Ochre City
    Ochre City is a popular nickname for Marrakesh, referring to the Moroccan city's distinctive red and ochre-colored buildings and walls.
  • C. Crown City
    Crown City is a nickname for Pasadena, California, highlighting its reputation as an elegant, historically rich city known for events like the Rose Parade.
  • D. Star City
    Star City is a commonly used nickname for the city of Lincoln, Nebraska.
  • E. Metroville
    Metroville is the fictional, modern American city that serves as the primary urban setting for Pixar’s superhero film "The Incredibles."
  • 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 City
Triple: [Cebu, hasPart, Bogo City]
Generated description
Bogo City is a component city in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding rural municipalities.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Bogo City
Target entity description: Bogo City is a component city in the northern part of Cebu province in the Philippines, known as a commercial and transport hub for surrounding rural municipalities.
  • A. South City
    South City is a colloquial name for South San Francisco, a suburban city in San Mateo County, California, known for its industrial history and proximity to San Francisco.
  • B. Ochre City
    Ochre City is a popular nickname for Marrakesh, referring to the Moroccan city's distinctive red and ochre-colored buildings and walls.
  • C. Crown City
    Crown City is a nickname for Pasadena, California, highlighting its reputation as an elegant, historically rich city known for events like the Rose Parade.
  • D. Star City
    Star City is a commonly used nickname for the city of Lincoln, Nebraska.
  • E. Metroville
    Metroville is the fictional, modern American city that serves as the primary urban setting for Pixar’s superhero film "The Incredibles."
  • 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_69a88a1554a48190a0180682bcf099be completed March 4, 2026, 7:37 p.m.
NER Named-entity recognition batch_69abc794eee481908163148e1e666d9b completed March 7, 2026, 6:37 a.m.
NED1 Entity disambiguation (via context triple) batch_69aea8ac3e80819099065f874f9dc25d completed March 9, 2026, 11:02 a.m.
NEDg Description generation batch_69aeabd9a5a08190a2c6699576e36c46 completed March 9, 2026, 11:15 a.m.
NED2 Entity disambiguation (via description) batch_69aead3299c88190af03577eef126387 completed March 9, 2026, 11:21 a.m.
Created at: March 4, 2026, 7:57 p.m.