Triple

T15002363
Position Surface form Disambiguated ID Type / Status
Subject Rio Rasina E374122 entity
Predicate tributaryOf P415 FINISHED
Object Chiascio River
The Chiascio River is a watercourse in central Italy that flows through the Umbria region and ultimately feeds into the Tiber River.
E1626829 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: Chiascio River | Statement: [Rio Rasina, tributaryOf, Chiascio 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: Chiascio River
Triple: [Rio Rasina, tributaryOf, Chiascio River]
Generated description
The Chiascio River is a watercourse in central Italy that flows through the Umbria region and ultimately feeds into the Tiber River.

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_69d85ccc84388190aa151e5173370c8d completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded7312ae48190bdaf91ecced6657e completed April 15, 2026, 12:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fc98202248190a2e3ee03c4e7078a completed May 22, 2026, 3:12 a.m.
NEDg Description generation batch_6a0fcade9db88190b79f8f03c9b5f51f completed May 22, 2026, 3:17 a.m.
NED2 Entity disambiguation (via description) batch_6a0fcb724a888190838a30e05e556421 completed May 22, 2026, 3:20 a.m.
Created at: April 10, 2026, 2:54 a.m.