Triple

T24972080
Position Surface form Disambiguated ID Type / Status
Subject Harrismith E624917 entity
Predicate hasNearby P350 FINISHED
Object Platberg mountain
Platberg mountain is a prominent flat-topped sandstone mountain overlooking the town of Harrismith in South Africa’s Free State province, known for its striking cliffs and popular hiking routes.
E1659948 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: Platberg mountain | Statement: [Harrismith, hasNearby, Platberg mountain]
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: Platberg mountain
Triple: [Harrismith, hasNearby, Platberg mountain]
Generated description
Platberg mountain is a prominent flat-topped sandstone mountain overlooking the town of Harrismith in South Africa’s Free State province, known for its striking cliffs and popular hiking routes.

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_69e2ff24512481908e9a72315b8d0354 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f444dd49648190a10956a729a40eec completed May 1, 2026, 6:14 a.m.
NED1 Entity disambiguation (via context triple) batch_6a103359fdf08190ad825bb2449d6241 completed May 22, 2026, 10:43 a.m.
NEDg Description generation batch_6a103440175081908c16266d18fa3f7f completed May 22, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a1034fb076881908947b97895c6bbc1 completed May 22, 2026, 10:50 a.m.
Created at: April 18, 2026, 6:01 a.m.