Triple

T25800058
Position Surface form Disambiguated ID Type / Status
Subject Yayabo River E649797 entity
Predicate hasMouthIn P1008 FINISHED
Object Zaza River
The Zaza River is a major river in central Cuba that flows through Sancti Spíritus Province and empties into the Caribbean Sea.
E2272181 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: Zaza River | Statement: [Yayabo River, hasMouthIn, Zaza 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: Zaza River
Triple: [Yayabo River, hasMouthIn, Zaza River]
Generated description
The Zaza River is a major river in central Cuba that flows through Sancti Spíritus Province and empties into the Caribbean Sea.

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_69e7ab34f8c8819099f6c4dabdabf129 completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5ffcaf4688190a22db6707856528d completed May 2, 2026, 1:44 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41d62f66108190a932d74bafeeec41 completed June 29, 2026, 2:19 a.m.
NEDg Description generation batch_6a41d6d79f9c8190ab63069d374deddd completed June 29, 2026, 2:22 a.m.
NED2 Entity disambiguation (via description) batch_6a41d72f88fc8190b5194d82e21e2da3 completed June 29, 2026, 2:23 a.m.
Created at: April 22, 2026, 6:36 a.m.