Triple

T23750684
Position Surface form Disambiguated ID Type / Status
Subject Tom Weiskopf E586954 entity
Predicate designedCourse P26143 FINISHED
Object Forest Highlands Golf Club
Forest Highlands Golf Club is a renowned private golf facility in Flagstaff, Arizona, featuring highly regarded mountain courses known for their scenic beauty and championship-caliber design.
E1627130 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: Forest Highlands Golf Club | Statement: [Tom Weiskopf, designedCourse, Forest Highlands 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: Forest Highlands Golf Club
Triple: [Tom Weiskopf, designedCourse, Forest Highlands Golf Club]
Generated description
Forest Highlands Golf Club is a renowned private golf facility in Flagstaff, Arizona, featuring highly regarded mountain courses known for their scenic beauty and championship-caliber 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_69e2490a0eec81908cdef8a862828d7a completed April 17, 2026, 2:51 p.m.
NER Named-entity recognition batch_69f1bcc1d4e8819099d3b4136f28f0c6 completed April 29, 2026, 8:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc98f70288190bc2b3896d4642f30 completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcb41ec208190ab3fb4e8b52c8c81 completed May 22, 2026, 3:19 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcbb4883c81909bb9f02361c69fe7 completed May 22, 2026, 3:21 a.m.
Created at: April 17, 2026, 7:13 p.m.