Triple

T25552039
Position Surface form Disambiguated ID Type / Status
Subject Argyle Falls E640466 entity
Predicate accessFrom P1985 FINISHED
Object Roxborough-Argyle Road
Roxborough-Argyle Road is a roadway in Tobago that runs through the island’s lush interior and serves as a key route to natural attractions such as Argyle Falls.
E1793063 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: Roxborough-Argyle Road | Statement: [Argyle Falls, accessFrom, Roxborough-Argyle Road]
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: Roxborough-Argyle Road
Triple: [Argyle Falls, accessFrom, Roxborough-Argyle Road]
Generated description
Roxborough-Argyle Road is a roadway in Tobago that runs through the island’s lush interior and serves as a key route to natural attractions such as Argyle Falls.

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_69e75dc101a881909fd33b02174e9768 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f8c65128819088bdee6fa1888bde completed May 2, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a13031af8c48190a46f24c02e47ac13 completed May 24, 2026, 1:54 p.m.
NEDg Description generation batch_6a13046b77f08190be1b607b8fe3f277 completed May 24, 2026, 2 p.m.
NED2 Entity disambiguation (via description) batch_6a1304efd82481909d557a7c07c29c9f completed May 24, 2026, 2:02 p.m.
Created at: April 21, 2026, 3:37 p.m.