Triple

T25546147
Position Surface form Disambiguated ID Type / Status
Subject Isabela, Puerto Rico E640309 entity
Predicate hasAttraction P105 FINISHED
Object Paseo Lineal Isabela
Paseo Lineal Isabela is a coastal recreational boardwalk and bike path in Isabela, Puerto Rico, known for its ocean views, beaches, and outdoor activities.
E1682264 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: Paseo Lineal Isabela | Statement: [Isabela, Puerto Rico, hasAttraction, Paseo Lineal Isabela]
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: Paseo Lineal Isabela
Triple: [Isabela, Puerto Rico, hasAttraction, Paseo Lineal Isabela]
Generated description
Paseo Lineal Isabela is a coastal recreational boardwalk and bike path in Isabela, Puerto Rico, known for its ocean views, beaches, and outdoor activities.

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_69e75dbfff7081909b0aa779d48321d2 completed April 21, 2026, 11:21 a.m.
NER Named-entity recognition batch_69f5f897fa5081909a0ff39571e22d98 completed May 2, 2026, 1:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10ad9c94c881908f65c080d227d597 completed May 22, 2026, 7:25 p.m.
NEDg Description generation batch_6a10ae9972908190ac6b8a2a0d6eb144 completed May 22, 2026, 7:29 p.m.
NED2 Entity disambiguation (via description) batch_6a10af2b626081908a1a67773654a991 completed May 22, 2026, 7:31 p.m.
Created at: April 21, 2026, 3:29 p.m.