Triple

T26685891
Position Surface form Disambiguated ID Type / Status
Subject Gelang Patah E672743 entity
Predicate partOf P40 FINISHED
Object Iskandar Puteri city
Iskandar Puteri city is a rapidly developing planned city in Johor, Malaysia, known as a key component of the Iskandar Malaysia economic corridor and a major administrative and commercial hub near Singapore.
E1737995 NE FINISHED

How this triple was built (2 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: Iskandar Puteri city | Statement: [Gelang Patah, partOf, Iskandar Puteri city]
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: Iskandar Puteri city
Triple: [Gelang Patah, partOf, Iskandar Puteri city]
Generated description
Iskandar Puteri city is a rapidly developing planned city in Johor, Malaysia, known as a key component of the Iskandar Malaysia economic corridor and a major administrative and commercial hub near Singapore.

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_69eecda2066c8190a344218afa5e89c1 completed April 27, 2026, 2:44 a.m.
NER Named-entity recognition batch_69f6173e191481909d1f6691a6fa8396 completed May 2, 2026, 3:24 p.m.
NED1 Entity disambiguation (via context triple) batch_6a11fe78262481909322a3c31687b486 completed May 23, 2026, 7:22 p.m.
NEDg Description generation batch_6a11ff4907e88190aaad22b7390bc094 completed May 23, 2026, 7:26 p.m.
NED2 Entity disambiguation (via description) batch_6a1200461b94819098a2cbd8b03d4076 completed May 23, 2026, 7:30 p.m.
Created at: April 27, 2026, 3:22 a.m.