Triple

T25735172
Position Surface form Disambiguated ID Type / Status
Subject Montagnana E645356 entity
Predicate locatedOnRiver P165 FINISHED
Object Frassine River
The Frassine River is a watercourse in northern Italy that flows through the Veneto region, including the area around the town of Montagnana.
 E2292644 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: Frassine River | Statement: [Montagnana, locatedOnRiver, Frassine River]
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: Frassine River
Triple: [Montagnana, locatedOnRiver, Frassine River]
Generated description
The Frassine River is a watercourse in northern Italy that flows through the Veneto region, including the area around the town of Montagnana.

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_69e77e85254081908d79ee4e8715f283 completed April 21, 2026, 1:41 p.m.
NER Named-entity recognition batch_69f5fcbead288190ad04ffa3c4d463be completed May 2, 2026, 1:31 p.m.
NED1 Entity disambiguation (via context triple) batch_6a79bed2ce9c8190961bda52af3bf4bc completed Aug. 10, 2026, 12:06 p.m.
NEDg Description generation batch_6a79c003094c819099f54190b81d1559 completed Aug. 10, 2026, 12:11 p.m.
NED2 Entity disambiguation (via description) batch_6a79c0a28f5c8190a73ca684d9848cf9 completed Aug. 10, 2026, 12:14 p.m.
Created at: April 21, 2026, 11:24 p.m.