Triple

T36775669
Position Surface form Disambiguated ID Type / Status
Subject Cadore E908611 entity
Predicate contains P35 FINISHED
Object Lorenzago di Cadore
Lorenzago di Cadore is a small mountain village and comune in the Veneto region of northern Italy, known for its scenic Dolomite setting and traditional Alpine character.
E2214300 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: Lorenzago di Cadore | Statement: [Cadore, contains, Lorenzago di Cadore]
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: Lorenzago di Cadore
Triple: [Cadore, contains, Lorenzago di Cadore]
Generated description
Lorenzago di Cadore is a small mountain village and comune in the Veneto region of northern Italy, known for its scenic Dolomite setting and traditional Alpine character.

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_69f76e798aa08190ace31098d1b13e9f completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69f7c9bd928081908734f5baece516bb completed May 3, 2026, 10:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3f69f769408190a51551d04c2e0d00 completed June 27, 2026, 6:13 a.m.
NEDg Description generation batch_6a3f6bcfe65c8190b9a9a81c79524d05 completed June 27, 2026, 6:21 a.m.
NED2 Entity disambiguation (via description) batch_6a3f6c554b188190b9f9e6122a2eeacf completed June 27, 2026, 6:23 a.m.
Created at: May 3, 2026, 4:12 p.m.