Triple

T27406884
Position Surface form Disambiguated ID Type / Status
Subject Río Laja E692025 entity
Predicate hasHydroelectricPlant P15311 FINISHED
Object Central Hidroeléctrica Abanico
Central Hidroeléctrica Abanico is a hydroelectric power plant in Chile that generates electricity using the flow of the Laja River.
E1777044 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: Central Hidroeléctrica Abanico | Statement: [Río Laja, hasHydroelectricPlant, Central Hidroeléctrica Abanico]
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: Central Hidroeléctrica Abanico
Triple: [Río Laja, hasHydroelectricPlant, Central Hidroeléctrica Abanico]
Generated description
Central Hidroeléctrica Abanico is a hydroelectric power plant in Chile that generates electricity using the flow of the Laja 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_69ef5205fc808190ad3efc5525b8e6d6 completed April 27, 2026, 12:09 p.m.
NER Named-entity recognition batch_69f62cd702e081909f5549c4aa6b837f completed May 2, 2026, 4:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12c597353481909adae2a865081f5a completed May 24, 2026, 9:32 a.m.
NEDg Description generation batch_6a12c6431ff8819092864b074cc494b8 completed May 24, 2026, 9:34 a.m.
NED2 Entity disambiguation (via description) batch_6a12c6c3a8fc819083942c89ff00352b completed May 24, 2026, 9:37 a.m.
Created at: April 27, 2026, 12:31 p.m.