Triple

T29733488
Position Surface form Disambiguated ID Type / Status
Subject Kota Setar District E752392 entity
Predicate hasJawiName P169325 FINISHED
Object دايره كوت ستار
دايره كوت ستار هو الاسم بالجَاوِي لمقاطعة كوتا ستار الإدارية الواقعة في ولاية كيدا بشمال ماليزيا.
 E1881733 NE FINISHED

How this triple was built (3 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: دايره كوت ستار | Statement: [Kota Setar District, hasJawiName, دايره كوت ستار]
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: دايره كوت ستار
Triple: [Kota Setar District, hasJawiName, دايره كوت ستار]
Generated description
دايره كوت ستار هو الاسم بالجَاوِي لمقاطعة كوتا ستار الإدارية الواقعة في ولاية كيدا بشمال ماليزيا.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: hasJawiName
Context triple: [Kota Setar District, hasJawiName, دايره كوت ستار]
  • A. hasJavaneseName
    Indicates that an entity possesses a name expressed in the Javanese language.
  • B. hasHangulName
    Indicates that an entity is associated with a name written in the Korean Hangul script.
  • C. hasMalayName
    Indicates that an entity is associated with a specific name expressed in the Malay language.
  • D. hasNameInKanji
    Indicates that an entity is associated with a specific written form of its name in Kanji characters.
  • E. hasNameInJapanese
    Indicates that an entity is associated with a specific name expressed in the Japanese language.
  • F. None of above. chosen

Provenance (7 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_69f0d62a36a88190bf860f00da433ff8 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f67de7792c81909b5e4e812d143624 completed May 2, 2026, 10:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26aa8879888190ac825323763e80bf completed June 8, 2026, 11:42 a.m.
NEDg Description generation batch_6a26b02c0ca88190b6b079c2f986de82 completed June 8, 2026, 12:06 p.m.
NED2 Entity disambiguation (via description) batch_6a26b4faf2c881909f77e6c4a8dc665b completed June 8, 2026, 12:26 p.m.
PD Predicate disambiguation batch_69f678ce54b081908c26edfd49e39c60 completed May 2, 2026, 10:21 p.m.
PDg Predicate description generation batch_69f67d31cc60819084f64bd056e1ea4d completed May 2, 2026, 10:39 p.m.
Created at: April 28, 2026, 7:44 p.m.