Triple

T22459638
Position Surface form Disambiguated ID Type / Status
Subject F. Springer E555195 entity
Predicate notableWork P4 FINISHED
Object Bandoeng-Bandung NE NERFINISHED

How this triple was built (2 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: Bandoeng-Bandung | Statement: [F. Springer, notableWork, Bandoeng-Bandung]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Bandoeng-Bandung
Context triple: [F. Springer, notableWork, Bandoeng-Bandung]
  • A. Bandung chosen
    Bandung is a large Indonesian city on the island of Java known for its cool climate, universities, colonial and art deco architecture, and role as a center of culture and technology.
  • B. Cimahi
    Cimahi is an urban city in Indonesia located near Bandung in the province of West Java, known historically as a military and training center.
  • C. Jatinangor
    Jatinangor is a town in West Java, Indonesia, known as a major educational hub hosting several prominent university campuses.
  • D. Tasikmalaya
    Tasikmalaya is a significant city in West Java, Indonesia, known as an important cultural and economic hub for the Sundanese people.
  • E. Cileunyi
    Cileunyi is a suburban district on the eastern outskirts of Bandung in West Java, Indonesia, known as a growing residential and transit area within the Bandung metropolitan region.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e11e51fdec8190adfdf9f8a6362221 completed April 16, 2026, 5:37 p.m.
NER Named-entity recognition batch_69f15b7e01fc8190825c3dc024484440 completed April 29, 2026, 1:14 a.m.
Created at: April 16, 2026, 8:48 p.m.