Triple

T27404036
Position Surface form Disambiguated ID Type / Status
Subject Teatinos River E691939 entity
Predicate nameInSpanish P2789 FINISHED
Object Río Teatinos
Río Teatinos is a river in Chile known for flowing through the Atacama Region and contributing to the hydrology of the country’s arid northern landscape.
 E2223253 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: Río Teatinos | Statement: [Teatinos River, nameInSpanish, Río Teatinos]
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: Río Teatinos
Triple: [Teatinos River, nameInSpanish, Río Teatinos]
Generated description
Río Teatinos is a river in Chile known for flowing through the Atacama Region and contributing to the hydrology of the country’s arid northern 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_69ef5205fc808190ad3efc5525b8e6d6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62cd4bd80819081454e99c3eec5a9 completed May 2, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a406cb47048819096c51142ec6deee5 completed June 28, 2026, 12:37 a.m.
NEDg Description generation batch_6a406db565b881909769124848e2b508 completed June 28, 2026, 12:41 a.m.
NED2 Entity disambiguation (via description) batch_6a406e2e5e00819097b90719f08951c8 completed June 28, 2026, 12:43 a.m.
Created at: April 27, 2026, 12:30 p.m.