Triple

T30302315
Position Surface form Disambiguated ID Type / Status
Subject Mount Seymour E770683 entity
Predicate hasHikingTrail P17835 FINISHED
Object Dog Mountain trail
Dog Mountain trail is a popular, relatively easy hiking route in British Columbia offering scenic forest walking and panoramic views near the summit of Mount Seymour.
E1907373 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: Dog Mountain trail | Statement: [Mount Seymour, hasHikingTrail, Dog Mountain 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: Dog Mountain trail
Triple: [Mount Seymour, hasHikingTrail, Dog Mountain trail]
Generated description
Dog Mountain trail is a popular, relatively easy hiking route in British Columbia offering scenic forest walking and panoramic views near the summit of Mount Seymour.

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_69f224881b948190b8c4921b250a44a3 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6813b03c881909786514932f103f3 completed May 2, 2026, 10:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a276f0e21d88190870816c1504204b1 completed June 9, 2026, 1:40 a.m.
NEDg Description generation batch_6a276febe8e48190a61b0e20ac44ab06 completed June 9, 2026, 1:44 a.m.
NED2 Entity disambiguation (via description) batch_6a27708bfc588190abd7fa5039f5153a completed June 9, 2026, 1:46 a.m.
Created at: April 29, 2026, 7:49 p.m.