Triple

T1477899
Position Surface form Disambiguated ID Type / Status
Subject Banten E30884 entity
Predicate hasMajorCity P316 FINISHED
Object Tangerang
Tangerang is a major urban and industrial city in Indonesia located just west of Jakarta on the island of Java.
 E185381 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: Tangerang | Statement: [Banten, hasMajorCity, Tangerang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tangerang
Context triple: [Banten, hasMajorCity, Tangerang]
  • A. Serang
    Serang is the capital city of Banten Province on the western tip of Java, Indonesia, serving as an important regional administrative and economic center.
  • B. Bekasi
    Bekasi is a large, rapidly growing industrial and residential city in the Greater Jakarta metropolitan area of Indonesia.
  • C. Bogor
    Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
  • D. Depok
    Depok is a rapidly growing commuter city in Indonesia located between Jakarta and Bogor, known for its universities and residential developments.
  • E. Bandar Lampung
    Bandar Lampung is a major port city in southern Sumatra, Indonesia, serving as the capital of Lampung Province and a key gateway between the island and Java.
  • 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: Tangerang
Triple: [Banten, hasMajorCity, Tangerang]
Generated description
Tangerang is a major urban and industrial city in Indonesia located just west of Jakarta on the island of Java.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tangerang
Target entity description: Tangerang is a major urban and industrial city in Indonesia located just west of Jakarta on the island of Java.
  • A. Serang
    Serang is the capital city of Banten Province on the western tip of Java, Indonesia, serving as an important regional administrative and economic center.
  • B. Bekasi
    Bekasi is a large, rapidly growing industrial and residential city in the Greater Jakarta metropolitan area of Indonesia.
  • C. Bogor
    Bogor is a city on the Indonesian island of Java known for its cool climate, botanical gardens, and role as a major educational and research center.
  • D. Depok
    Depok is a rapidly growing commuter city in Indonesia located between Jakarta and Bogor, known for its universities and residential developments.
  • E. Bandar Lampung
    Bandar Lampung is a major port city in southern Sumatra, Indonesia, serving as the capital of Lampung Province and a key gateway between the island and Java.
  • 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_69a498fe55a88190ab7f9e40ace88e49 completed March 1, 2026, 7:52 p.m.
NER Named-entity recognition batch_69a4c605d4c0819088ab06678b2ba6f3 completed March 1, 2026, 11:04 p.m.
NED1 Entity disambiguation (via context triple) batch_69ad58b487c08190bb2b1c259bd39db0 completed March 8, 2026, 11:08 a.m.
NEDg Description generation batch_69ad5c73d7fc8190a2983c2a33b2ce01 completed March 8, 2026, 11:24 a.m.
NED2 Entity disambiguation (via description) batch_69ad5cf99a908190b8af9e7bb1949d80 completed March 8, 2026, 11:26 a.m.
Created at: March 1, 2026, 8:11 p.m.