Triple

T1336563
Position Surface form Disambiguated ID Type / Status
Subject Yogyakarta E28762 entity
Predicate hasNickname P39 FINISHED
Object Kota Pelajar
Kota Pelajar is a popular nickname for Yogyakarta, Indonesia, highlighting its status as a major national center of education and student life.
E154817 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: Kota Pelajar | Statement: [Yogyakarta, hasNickname, Kota Pelajar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Kota Pelajar
Context triple: [Yogyakarta, hasNickname, Kota Pelajar]
  • A. Kota
    Kota is a major industrial and educational city in southeastern Rajasthan, India, known for its coaching institutes and power plants along the Chambal River.
  • B. Città universitaria
    Città universitaria is the main university district in Rome that houses the central campus and key facilities of Sapienza University.
  • C. Kokota
    Kokota is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • D. Óbuda University
    Óbuda University is a Hungarian public university in Budapest known for its strong focus on engineering, applied sciences, and technical education.
  • E. Komaba Campus
    Komaba Campus is a major campus of the University of Tokyo, known for hosting the College of Arts and Sciences and many first- and second-year undergraduate programs.
  • 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: Kota Pelajar
Triple: [Yogyakarta, hasNickname, Kota Pelajar]
Generated description
Kota Pelajar is a popular nickname for Yogyakarta, Indonesia, highlighting its status as a major national center of education and student life.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Kota Pelajar
Target entity description: Kota Pelajar is a popular nickname for Yogyakarta, Indonesia, highlighting its status as a major national center of education and student life.
  • A. Kota
    Kota is a major industrial and educational city in southeastern Rajasthan, India, known for its coaching institutes and power plants along the Chambal River.
  • B. Città universitaria
    Città universitaria is the main university district in Rome that houses the central campus and key facilities of Sapienza University.
  • C. Kokota
    Kokota is an Oceanic language spoken in the Solomon Islands, particularly on Santa Isabel Island.
  • D. Óbuda University
    Óbuda University is a Hungarian public university in Budapest known for its strong focus on engineering, applied sciences, and technical education.
  • E. Komaba Campus
    Komaba Campus is a major campus of the University of Tokyo, known for hosting the College of Arts and Sciences and many first- and second-year undergraduate programs.
  • 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_69a498561a508190a3e1bc137c2b866a completed March 1, 2026, 7:49 p.m.
NER Named-entity recognition batch_69a4c1edda1c81909a1149b254b0d57e completed March 1, 2026, 10:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69acc62b9bd081909dbe22cbea03f21f completed March 8, 2026, 12:43 a.m.
NEDg Description generation batch_69acc6c204a88190a3171898e6e1bb91 completed March 8, 2026, 12:45 a.m.
NED2 Entity disambiguation (via description) batch_69acc7d8df108190bf92ca5e33987d04 completed March 8, 2026, 12:50 a.m.
Created at: March 1, 2026, 7:55 p.m.