Triple

T23430151
Position Surface form Disambiguated ID Type / Status
Subject Los Alerces National Park E563303 entity
Predicate hasLake P1025 FINISHED
Object Futalaufquen Lake
Futalaufquen Lake is a scenic glacial lake in Argentine Patagonia, renowned for its clear waters, surrounding Andean forests, and popularity for fishing and outdoor recreation.
E2054706 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: Futalaufquen Lake | Statement: [Los Alerces National Park, hasLake, Futalaufquen Lake]
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: Futalaufquen Lake
Triple: [Los Alerces National Park, hasLake, Futalaufquen Lake]
Generated description
Futalaufquen Lake is a scenic glacial lake in Argentine Patagonia, renowned for its clear waters, surrounding Andean forests, and popularity for fishing and outdoor recreation.

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_69e24553980c8190bb66a2ae0bdab125 completed April 17, 2026, 2:36 p.m.
NER Named-entity recognition batch_69f1a5d6d1c881908e3c4ac0e7cd30cd completed April 29, 2026, 6:31 a.m.
NED1 Entity disambiguation (via context triple) batch_6a35a64b23ec8190938f1ae72efbec59 completed June 19, 2026, 8:27 p.m.
NEDg Description generation batch_6a35a6bf0bb08190878fe21fa3c6d5ea completed June 19, 2026, 8:29 p.m.
NED2 Entity disambiguation (via description) batch_6a35a731ae0c8190a71409322d9c5ad0 completed June 19, 2026, 8:31 p.m.
Created at: April 17, 2026, 5:48 p.m.