Triple

T8340238
Position Surface form Disambiguated ID Type / Status
Subject South Jakarta E195890 entity
Predicate contains P35 FINISHED
Object Tebet
Tebet is a densely populated urban district in South Jakarta, Indonesia, known for its residential neighborhoods, commercial areas, and busy traffic corridors.
 E727960 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: Tebet | Statement: [South Jakarta, contains, Tebet]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tebet
Context triple: [South Jakarta, contains, Tebet]
  • A. Takrur
    Takrur was an early West African kingdom located in the Senegal River valley, known for its role in trans-Saharan trade and its early adoption of Islam.
  • B. Touqan
    Touqan is a family name of notable Palestinian origin, associated with prominent poets, politicians, and intellectuals in the Arab world.
  • C. Tawilis
    Tawilis is a small freshwater sardine species found only in the Philippines’ Taal Lake and is notable as the world’s only known freshwater sardine.
  • D. Tissi
    Tissi is a small municipality in the Sardinia region of Italy, located in the province of Sassari.
  • E. Gebal
    Gebal is the ancient name of the Phoenician coastal city later known as Byblos, one of the oldest continuously inhabited cities in the world.
  • 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: Tebet
Triple: [South Jakarta, contains, Tebet]
Generated description
Tebet is a densely populated urban district in South Jakarta, Indonesia, known for its residential neighborhoods, commercial areas, and busy traffic corridors.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tebet
Target entity description: Tebet is a densely populated urban district in South Jakarta, Indonesia, known for its residential neighborhoods, commercial areas, and busy traffic corridors.
  • A. Takrur
    Takrur was an early West African kingdom located in the Senegal River valley, known for its role in trans-Saharan trade and its early adoption of Islam.
  • B. Touqan
    Touqan is a family name of notable Palestinian origin, associated with prominent poets, politicians, and intellectuals in the Arab world.
  • C. Tawilis
    Tawilis is a small freshwater sardine species found only in the Philippines’ Taal Lake and is notable as the world’s only known freshwater sardine.
  • D. Tissi
    Tissi is a small municipality in the Sardinia region of Italy, located in the province of Sassari.
  • E. Gebal
    Gebal is the ancient name of the Phoenician coastal city later known as Byblos, one of the oldest continuously inhabited cities in the world.
  • 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_69ca82ecbdc481908a55cad8ca062d88 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7fd7a3888190b54306ed862aded4 completed March 31, 2026, 8:03 a.m.
NED1 Entity disambiguation (via context triple) batch_69cdc7237aa0819092b3679a318223ba completed April 2, 2026, 1:32 a.m.
NEDg Description generation batch_69cdcc8439cc8190b00ce9b0781d0544 completed April 2, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_69cdcdd1a0c08190aa15e665a38945e7 completed April 2, 2026, 2 a.m.
Created at: March 30, 2026, 5:57 p.m.