Triple

T24708806
Position Surface form Disambiguated ID Type / Status
Subject Lago di Campotosto E611971 entity
Predicate locatedInMunicipality P40 FINISHED
Object Capitignano
Capitignano is a small municipality in Italy’s Abruzzo region, known for its proximity to the artificial mountain lake Lago di Campotosto and its scenic Apennine landscape.
E1660963 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: Capitignano | Statement: [Lago di Campotosto, locatedInMunicipality, Capitignano]
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: Capitignano
Triple: [Lago di Campotosto, locatedInMunicipality, Capitignano]
Generated description
Capitignano is a small municipality in Italy’s Abruzzo region, known for its proximity to the artificial mountain lake Lago di Campotosto and its scenic Apennine landscape.

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_69e2c4d9c24c8190a3712d74327f0c6e completed April 17, 2026, 11:40 p.m.
NER Named-entity recognition batch_69f40ff8681c8190a8a8168dd75c5ded completed May 1, 2026, 2:29 a.m.
NED1 Entity disambiguation (via context triple) batch_6a10487b26488190aeb1e52f2405ad78 completed May 22, 2026, 12:13 p.m.
NEDg Description generation batch_6a1049b63de881908e04b30b555d7809 completed May 22, 2026, 12:19 p.m.
NED2 Entity disambiguation (via description) batch_6a104a7bba188190b4d819ed6c618086 completed May 22, 2026, 12:22 p.m.
Created at: April 18, 2026, 3:24 a.m.