Triple

T25872459
Position Surface form Disambiguated ID Type / Status
Subject Linville, North Carolina E651794 entity
Predicate hasAttraction P105 FINISHED
Object Linville Golf Club
Linville Golf Club is a historic, high-elevation mountain golf course in Linville, North Carolina, known for its scenic Blue Ridge setting and classic Donald Ross design.
E1700614 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: Linville Golf Club | Statement: [Linville, North Carolina, hasAttraction, Linville Golf Club]
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: Linville Golf Club
Triple: [Linville, North Carolina, hasAttraction, Linville Golf Club]
Generated description
Linville Golf Club is a historic, high-elevation mountain golf course in Linville, North Carolina, known for its scenic Blue Ridge setting and classic Donald Ross design.

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_69e7ab3ad9d88190841ddcb93ab02e96 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f602dd86dc8190b36335017d158398 completed May 2, 2026, 1:57 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ecb22dec8190bbc3eff54c86d743 completed May 22, 2026, 11:54 p.m.
NEDg Description generation batch_6a10edc67f448190b6f8da9b63fd6759 completed May 22, 2026, 11:59 p.m.
NED2 Entity disambiguation (via description) batch_6a10ef3e35188190806530f76d78e331 completed May 23, 2026, 12:05 a.m.
Created at: April 22, 2026, 8:11 a.m.