Triple

T37752684
Position Surface form Disambiguated ID Type / Status
Subject Nibong Tebal E941022 entity
Predicate parliamentaryConstituency P2710 FINISHED
Object Nibong Tebal (federal constituency)
Nibong Tebal (federal constituency) is a Malaysian electoral district in Penang represented in the Dewan Rakyat, known for encompassing a mix of semi-urban and industrial areas.
E2241887 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: Nibong Tebal (federal constituency) | Statement: [Nibong Tebal, parliamentaryConstituency, Nibong Tebal (federal constituency)]
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: Nibong Tebal (federal constituency)
Triple: [Nibong Tebal, parliamentaryConstituency, Nibong Tebal (federal constituency)]
Generated description
Nibong Tebal (federal constituency) is a Malaysian electoral district in Penang represented in the Dewan Rakyat, known for encompassing a mix of semi-urban and industrial areas.

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_69f76ee1f3a88190834e6c8af99bccc9 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fbaef25db48190a145b2533b39f846 completed May 6, 2026, 9:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40e0799e9881909a9fcd1b470f0110 completed June 28, 2026, 8:51 a.m.
NEDg Description generation batch_6a40e13e5b4c8190b8cd2c02b2e09398 completed June 28, 2026, 8:54 a.m.
NED2 Entity disambiguation (via description) batch_6a40e4337dc48190b4499e218740a793 completed June 28, 2026, 9:06 a.m.
Created at: May 3, 2026, 4:19 p.m.