Triple

T35074545
Position Surface form Disambiguated ID Type / Status
Subject Arrecifes sector E1011973 entity
Predicate accessPointFor P5347 FINISHED
Object El Cabo trail
El Cabo trail is a popular coastal hiking route in Tayrona National Natural Park in Colombia, leading through tropical forest and beaches to the scenic Cabo San Juan area.
E2125109 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: El Cabo trail | Statement: [Arrecifes sector, accessPointFor, El Cabo trail]
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: El Cabo trail
Triple: [Arrecifes sector, accessPointFor, El Cabo trail]
Generated description
El Cabo trail is a popular coastal hiking route in Tayrona National Natural Park in Colombia, leading through tropical forest and beaches to the scenic Cabo San Juan area.

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_69f76dd193108190af2528186f25b72a completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7865a08408190af85d3620b509e67 completed May 3, 2026, 5:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a37c646b83c819093212ae8495507c0 completed June 21, 2026, 11:08 a.m.
NEDg Description generation batch_6a37c6e970f48190b35c179e766c58cc completed June 21, 2026, 11:11 a.m.
NED2 Entity disambiguation (via description) batch_6a37cad6f71c81908794928c0e20ab20 completed June 21, 2026, 11:28 a.m.
Created at: May 3, 2026, 4:01 p.m.