Triple

T1853048
Position Surface form Disambiguated ID Type / Status
Subject Kelantan E41638 entity
Predicate hasTown P847 FINISHED
Object Tanah Merah
Tanah Merah is a town in the Malaysian state of Kelantan, known as a regional commercial and administrative center.
E205058 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: Tanah Merah | Statement: [Kelantan, hasTown, Tanah Merah]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tanah Merah
Context triple: [Kelantan, hasTown, Tanah Merah]
  • A. Marapu
    Marapu is the indigenous ancestral belief system of the Sumbanese people, characterized by animism, ancestor worship, and elaborate ritual practices.
  • B. Shabara
    Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
  • C. Areia
    Areia is a historic colonial-era city in the Brazilian state of Paraíba, known for its preserved architecture and cultural heritage.
  • D. Areias
    Areias is a neighborhood within the city of Recife, Brazil, known as part of its urban residential area.
  • E. Las Breas
    Las Breas is a small settlement located within the Río Hurtado area of Chile, likely characterized by its rural Andean setting and agricultural activities.
  • 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: Tanah Merah
Triple: [Kelantan, hasTown, Tanah Merah]
Generated description
Tanah Merah is a town in the Malaysian state of Kelantan, known as a regional commercial and administrative center.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Tanah Merah
Target entity description: Tanah Merah is a town in the Malaysian state of Kelantan, known as a regional commercial and administrative center.
  • A. Marapu
    Marapu is the indigenous ancestral belief system of the Sumbanese people, characterized by animism, ancestor worship, and elaborate ritual practices.
  • B. Shabara
    Shabara was an early Indian philosopher and commentator best known for his influential exegesis on the Purva Mimamsa school of Hindu philosophy.
  • C. Areia
    Areia is a historic colonial-era city in the Brazilian state of Paraíba, known for its preserved architecture and cultural heritage.
  • D. Areias
    Areias is a neighborhood within the city of Recife, Brazil, known as part of its urban residential area.
  • E. Las Breas
    Las Breas is a small settlement located within the Río Hurtado area of Chile, likely characterized by its rural Andean setting and agricultural activities.
  • 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_69a8864a83848190a4ec02721306c511 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69abb06999f4819086386aafb789a368 completed March 7, 2026, 4:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69adc9c81f2c81908339f6a1d1987631 completed March 8, 2026, 7:11 p.m.
NEDg Description generation batch_69adcb1565a881908dfc906654429e3f completed March 8, 2026, 7:16 p.m.
NED2 Entity disambiguation (via description) batch_69adcbbc8a108190ad77e91f2ec14b8f completed March 8, 2026, 7:19 p.m.
Created at: March 4, 2026, 7:33 p.m.