Triple

T24579113
Position Surface form Disambiguated ID Type / Status
Subject Wilson, North Carolina E608196 entity
Predicate hasAttraction P105 FINISHED
Object Wilson Botanical Gardens
Wilson Botanical Gardens is a public botanical garden in Wilson, North Carolina, featuring diverse plant collections, themed gardens, and educational displays for visitors.
E1640460 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: Wilson Botanical Gardens | Statement: [Wilson, North Carolina, hasAttraction, Wilson Botanical Gardens]
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: Wilson Botanical Gardens
Triple: [Wilson, North Carolina, hasAttraction, Wilson Botanical Gardens]
Generated description
Wilson Botanical Gardens is a public botanical garden in Wilson, North Carolina, featuring diverse plant collections, themed gardens, and educational displays for visitors.

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_69e2c4cdab6c8190aae6e5d3de55c95e completed April 17, 2026, 11:39 p.m.
NER Named-entity recognition batch_69f2a97cd0d4819091bf0841fa8e108a completed April 30, 2026, 12:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0ff87465988190bc435c2dc2d80c0a completed May 22, 2026, 6:32 a.m.
NEDg Description generation batch_6a0ff956f6e48190950c5bace85c9669 completed May 22, 2026, 6:36 a.m.
NED2 Entity disambiguation (via description) batch_6a0ffa00b57081909bc69474734fcb20 completed May 22, 2026, 6:38 a.m.
Created at: April 18, 2026, 2:29 a.m.