Triple

T24962317
Position Surface form Disambiguated ID Type / Status
Subject Passo Falzarego E624641 entity
Predicate near P350 FINISHED
Object Lagazuoi
Lagazuoi is a mountain in the Dolomites of northern Italy, renowned for its World War I tunnels, panoramic hiking routes, and popular ski area.
E1656490 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: Lagazuoi | Statement: [Passo Falzarego, near, Lagazuoi]
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: Lagazuoi
Triple: [Passo Falzarego, near, Lagazuoi]
Generated description
Lagazuoi is a mountain in the Dolomites of northern Italy, renowned for its World War I tunnels, panoramic hiking routes, and popular ski 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_69e2ff23a3a88190b1b9743fe5e15f94 completed April 18, 2026, 3:48 a.m.
NER Named-entity recognition batch_69f4242e3fd08190bc08e46222fb2c67 completed May 1, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a103352b14481908d4db829007d1482 completed May 22, 2026, 10:43 a.m.
NEDg Description generation batch_6a10343efd288190884ee9ebcb1b4afb completed May 22, 2026, 10:47 a.m.
NED2 Entity disambiguation (via description) batch_6a1034f2e0b88190b296a251056bce15 completed May 22, 2026, 10:50 a.m.
Created at: April 18, 2026, 5:59 a.m.