Triple

T11624601
Position Surface form Disambiguated ID Type / Status
Subject Seremban E276229 entity
Predicate hasSubdivision P747 FINISHED
Object Seremban Jaya
Seremban Jaya is a residential and commercial township located within the city of Seremban in the state of Negeri Sembilan, Malaysia.
E940007 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: Seremban Jaya | Statement: [Seremban, hasSubdivision, Seremban Jaya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seremban Jaya
Context triple: [Seremban, hasSubdivision, Seremban Jaya]
  • A. Seremban
    Seremban is the capital city of the Malaysian state of Negeri Sembilan, known as an administrative, commercial, and cultural center in the western part of Peninsular Malaysia.
  • B. Ampang Jaya
    Ampang Jaya is a suburban municipality in the state of Selangor, Malaysia, forming part of the greater Kuala Lumpur metropolitan area.
  • C. Temerloh
    Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
  • D. Gombak
    Gombak is a district in the state of Selangor, Malaysia, located within the greater Kuala Lumpur metropolitan area in the Klang Valley.
  • E. Semenyih
    Semenyih is a rapidly developing town in the state of Selangor, Malaysia, known for its residential growth, educational institutions, and proximity to Kuala Lumpur within the greater Klang Valley region.
  • 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: Seremban Jaya
Triple: [Seremban, hasSubdivision, Seremban Jaya]
Generated description
Seremban Jaya is a residential and commercial township located within the city of Seremban in the state of Negeri Sembilan, Malaysia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Seremban Jaya
Target entity description: Seremban Jaya is a residential and commercial township located within the city of Seremban in the state of Negeri Sembilan, Malaysia.
  • A. Seremban
    Seremban is the capital city of the Malaysian state of Negeri Sembilan, known as an administrative, commercial, and cultural center in the western part of Peninsular Malaysia.
  • B. Ampang Jaya
    Ampang Jaya is a suburban municipality in the state of Selangor, Malaysia, forming part of the greater Kuala Lumpur metropolitan area.
  • C. Temerloh
    Temerloh is a town in central Pahang, Malaysia, known as a regional commercial hub and gateway to the state's interior.
  • D. Gombak
    Gombak is a district in the state of Selangor, Malaysia, located within the greater Kuala Lumpur metropolitan area in the Klang Valley.
  • E. Semenyih
    Semenyih is a rapidly developing town in the state of Selangor, Malaysia, known for its residential growth, educational institutions, and proximity to Kuala Lumpur within the greater Klang Valley region.
  • 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_69d6aafa51148190ab84940694c00235 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a12416908190ac2dcd7f7ebb308f completed April 10, 2026, 7:05 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef13491c0c819085f4ea17ad74612a completed April 27, 2026, 7:42 a.m.
NEDg Description generation batch_69ef354b3b3c8190b1c91dbf9c705a7d completed April 27, 2026, 10:07 a.m.
NED2 Entity disambiguation (via description) batch_69ef5170ce9881908f2ecf3d5ada809a completed April 27, 2026, 12:07 p.m.
Created at: April 8, 2026, 9:39 p.m.