Triple

T11787058
Position Surface form Disambiguated ID Type / Status
Subject Kuala Terengganu E280295 entity
Predicate hasLandmark P105 FINISHED
Object Pasar Payang
Pasar Payang is a famous central market in Kuala Terengganu known for its bustling atmosphere, traditional handicrafts, and local food products.
E946482 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: Pasar Payang | Statement: [Kuala Terengganu, hasLandmark, Pasar Payang]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Pasar Payang
Context triple: [Kuala Terengganu, hasLandmark, Pasar Payang]
  • A. Pasar Rebo
    Pasar Rebo is a district in East Jakarta, Indonesia, known for its traditional market and residential neighborhoods.
  • B. Pasar Minggu
    Pasar Minggu is a district in South Jakarta, Indonesia, known for its traditional market, residential neighborhoods, and busy commercial areas.
  • C. Pasir Mas
    Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
  • D. Bandar Lengeh
    Bandar Lengeh is a coastal city and important maritime port on the Persian Gulf in southern Iran’s Hormozgan Province.
  • E. Padang Bai
    Padang Bai is a small coastal village and port in eastern Bali, Indonesia, known as a gateway to the nearby islands and for its beaches and dive sites.
  • 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: Pasar Payang
Triple: [Kuala Terengganu, hasLandmark, Pasar Payang]
Generated description
Pasar Payang is a famous central market in Kuala Terengganu known for its bustling atmosphere, traditional handicrafts, and local food products.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Pasar Payang
Target entity description: Pasar Payang is a famous central market in Kuala Terengganu known for its bustling atmosphere, traditional handicrafts, and local food products.
  • A. Pasar Rebo
    Pasar Rebo is a district in East Jakarta, Indonesia, known for its traditional market and residential neighborhoods.
  • B. Pasar Minggu
    Pasar Minggu is a district in South Jakarta, Indonesia, known for its traditional market, residential neighborhoods, and busy commercial areas.
  • C. Pasir Mas
    Pasir Mas is a town in the Malaysian state of Kelantan, known as a local commercial and transport hub near the border with Thailand.
  • D. Bandar Lengeh
    Bandar Lengeh is a coastal city and important maritime port on the Persian Gulf in southern Iran’s Hormozgan Province.
  • E. Padang Bai
    Padang Bai is a small coastal village and port in eastern Bali, Indonesia, known as a gateway to the nearby islands and for its beaches and dive sites.
  • 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_69d6ab258b808190b1735835c841e3a4 completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d8a586803481909af0032c35ca6e51 completed April 10, 2026, 7:23 a.m.
NED1 Entity disambiguation (via context triple) batch_69f090e8828481908baa7f6067190db3 completed April 28, 2026, 10:50 a.m.
NEDg Description generation batch_69f0bd3f39608190b29027b30664bd9c completed April 28, 2026, 1:59 p.m.
NED2 Entity disambiguation (via description) batch_69f0ef5afd448190953b5d9929478132 completed April 28, 2026, 5:33 p.m.
Created at: April 8, 2026, 9:42 p.m.