Triple

T37436507
Position Surface form Disambiguated ID Type / Status
Subject Kat River E930287 entity
Predicate locatedIn P40 FINISHED
Object Fort Beaufort Local Municipality
Fort Beaufort Local Municipality was a former local government area in South Africa’s Eastern Cape province, centered on the town of Fort Beaufort and surrounding rural communities.
E2227269 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: Fort Beaufort Local Municipality | Statement: [Kat River, locatedIn, Fort Beaufort Local Municipality]
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: Fort Beaufort Local Municipality
Triple: [Kat River, locatedIn, Fort Beaufort Local Municipality]
Generated description
Fort Beaufort Local Municipality was a former local government area in South Africa’s Eastern Cape province, centered on the town of Fort Beaufort and surrounding rural communities.

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_69f76ebfdcb8819098562ff3db673b04 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb8dd68ea48190a17bb07d0b509435 completed May 6, 2026, 6:52 p.m.
NED1 Entity disambiguation (via context triple) batch_6a40825702f4819091244669a2a98c55 completed June 28, 2026, 2:09 a.m.
NEDg Description generation batch_6a4083d4e4488190bb8dbb8814365aeb completed June 28, 2026, 2:15 a.m.
NED2 Entity disambiguation (via description) batch_6a40845a16388190b73252a9bce66c34 completed June 28, 2026, 2:18 a.m.
Created at: May 3, 2026, 4:17 p.m.