Triple

T34837312
Position Surface form Disambiguated ID Type / Status
Subject Forillon National Park E1004235 entity
Predicate hasTrail P3625 FINISHED
Object Les Graves trail
Les Graves trail is a scenic hiking route in Forillon National Park in Quebec, Canada, known for its coastal views, cliffs, and opportunities to see marine wildlife.
E2117530 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: Les Graves trail | Statement: [Forillon National Park, hasTrail, Les Graves 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: Les Graves trail
Triple: [Forillon National Park, hasTrail, Les Graves trail]
Generated description
Les Graves trail is a scenic hiking route in Forillon National Park in Quebec, Canada, known for its coastal views, cliffs, and opportunities to see marine wildlife.

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_69f76db97714819099b5bed36fd64e9d completed May 3, 2026, 3:46 p.m.
NER Named-entity recognition batch_69f7810f5bdc8190b3f7c714f17eefce completed May 3, 2026, 5:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3786c9f8a48190a5ba17b600feb679 completed June 21, 2026, 6:38 a.m.
NEDg Description generation batch_6a378abf1b0481909040f688fadcf447 completed June 21, 2026, 6:54 a.m.
NED2 Entity disambiguation (via description) batch_6a378bc690f08190970e7b189ff9627c completed June 21, 2026, 6:59 a.m.
Created at: May 3, 2026, 4 p.m.