Triple

T29657249
Position Surface form Disambiguated ID Type / Status
Subject Segamat District E750301 entity
Predicate borderedBy P224 FINISHED
Object Rompin District (Pahang)
Rompin District is a largely rural coastal district in southeastern Pahang, Malaysia, known for its fishing communities, beaches, and proximity to natural attractions such as Endau-Rompin National Park.
E1876780 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: Rompin District (Pahang) | Statement: [Segamat District, borderedBy, Rompin District (Pahang)]
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: Rompin District (Pahang)
Triple: [Segamat District, borderedBy, Rompin District (Pahang)]
Generated description
Rompin District is a largely rural coastal district in southeastern Pahang, Malaysia, known for its fishing communities, beaches, and proximity to natural attractions such as Endau-Rompin National Park.

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_69f0d6226fe881908819197c9ef9ee04 completed April 28, 2026, 3:45 p.m.
NER Named-entity recognition batch_69f66f2850288190a394272ae49084e3 completed May 2, 2026, 9:39 p.m.
NED1 Entity disambiguation (via context triple) batch_6a26618b7fe881909c2bb6681ef65217 completed June 8, 2026, 6:30 a.m.
NEDg Description generation batch_6a26656b2d208190aeda49d3fdadd561 completed June 8, 2026, 6:47 a.m.
NED2 Entity disambiguation (via description) batch_6a266abade508190ad7a5d6c034cc354 completed June 8, 2026, 7:09 a.m.
Created at: April 28, 2026, 6:56 p.m.