Triple

T30724850
Position Surface form Disambiguated ID Type / Status
Subject Bukit Kayu Hitam E782249 entity
Predicate partOf P40 FINISHED
Object Malaysia–Thailand road network
The Malaysia–Thailand road network is a system of highways and border crossings that links major towns and trade routes between Malaysia and Thailand, facilitating cross-border transport and commerce.
E1928791 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: Malaysia–Thailand road network | Statement: [Bukit Kayu Hitam, partOf, Malaysia–Thailand road network]
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: Malaysia–Thailand road network
Triple: [Bukit Kayu Hitam, partOf, Malaysia–Thailand road network]
Generated description
The Malaysia–Thailand road network is a system of highways and border crossings that links major towns and trade routes between Malaysia and Thailand, facilitating cross-border transport and commerce.

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_69f224ad9f9c81908e02a79ae0001137 completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f68c5bab9c8190b1f0518559c5259f completed May 2, 2026, 11:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a28990dd09081909b6069fd4d180873 completed June 9, 2026, 10:51 p.m.
NEDg Description generation batch_6a2899a6b1488190add895dfe8a2f52f completed June 9, 2026, 10:54 p.m.
NED2 Entity disambiguation (via description) batch_6a289aff92fc81908aecbb572c0250c1 completed June 9, 2026, 11 p.m.
Created at: April 29, 2026, 8:36 p.m.