Triple

T13012452
Position Surface form Disambiguated ID Type / Status
Subject Nezu E322452 entity
Predicate hasNearbyArea P4647 FINISHED
Object Hongo
Hongo is a historic district in Bunkyo, Tokyo, known for its academic institutions, including the main campus of the University of Tokyo.
E1015491 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: Hongo | Statement: [Nezu, hasNearbyArea, Hongo]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Hongo
Context triple: [Nezu, hasNearbyArea, Hongo]
  • A. Gomba
    Gomba is a district within the Buganda region of central Uganda, known primarily for its rural communities and agricultural activities.
  • B. Fungo
    Fungo is the costumed team mascot of the New Hampshire Fisher Cats minor league baseball club, entertaining fans at games and community events.
  • C. Myko
    Myko is a short, informal given name or nickname derived from the Slavic name Mykola.
  • D. Kungara
    Kungara is an alternative name for the Fur language, a Nilo-Saharan language spoken primarily by the Fur people of western Sudan.
  • E. Mukrang
    Mukrang is a principal deity revered in the Hemphu-Mukrang religious tradition of the Karbi people of Northeast India.
  • 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: Hongo
Triple: [Nezu, hasNearbyArea, Hongo]
Generated description
Hongo is a historic district in Bunkyo, Tokyo, known for its academic institutions, including the main campus of the University of Tokyo.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Hongo
Target entity description: Hongo is a historic district in Bunkyo, Tokyo, known for its academic institutions, including the main campus of the University of Tokyo.
  • A. Gomba
    Gomba is a district within the Buganda region of central Uganda, known primarily for its rural communities and agricultural activities.
  • B. Fungo
    Fungo is the costumed team mascot of the New Hampshire Fisher Cats minor league baseball club, entertaining fans at games and community events.
  • C. Myko
    Myko is a short, informal given name or nickname derived from the Slavic name Mykola.
  • D. Kungara
    Kungara is an alternative name for the Fur language, a Nilo-Saharan language spoken primarily by the Fur people of western Sudan.
  • E. Mukrang
    Mukrang is a principal deity revered in the Hemphu-Mukrang religious tradition of the Karbi people of Northeast India.
  • 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_69d807657e8c8190bd9435ee2f823845 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69d97ecbb8f4819094d55eb07cb5ad97 completed April 10, 2026, 10:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69f6c10d5b9881909db688c1ab0e6a77 completed May 3, 2026, 3:29 a.m.
NEDg Description generation batch_69f6c277e6248190870b3bf9869716a7 completed May 3, 2026, 3:35 a.m.
NED2 Entity disambiguation (via description) batch_69f6c38bc0b08190b76cb0853d99ad82 completed May 3, 2026, 3:39 a.m.
Created at: April 9, 2026, 8:49 p.m.