Triple

T24454416
Position Surface form Disambiguated ID Type / Status
Subject Municipality of Jayuya E616640 entity
Predicate namedAfter P63 FINISHED
Object Taíno leader Hayuya
Taíno leader Hayuya was an indigenous chief (cacique) of pre-Columbian Puerto Rico whose legacy is commemorated in the naming of the municipality of Jayuya.
E1636253 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: Taíno leader Hayuya | Statement: [Municipality of Jayuya, namedAfter, Taíno leader Hayuya]
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: Taíno leader Hayuya
Triple: [Municipality of Jayuya, namedAfter, Taíno leader Hayuya]
Generated description
Taíno leader Hayuya was an indigenous chief (cacique) of pre-Columbian Puerto Rico whose legacy is commemorated in the naming of the municipality of Jayuya.

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_69e2d7ef9fe08190a0613908758b4e86 completed April 18, 2026, 1:01 a.m.
NER Named-entity recognition batch_69f298c4f1d881909d9119fec74afe53 completed April 29, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe388ff60819082e5eee872240764 completed May 22, 2026, 5:03 a.m.
NEDg Description generation batch_6a0fe7dc05c48190b1570218f6f30d9a completed May 22, 2026, 5:21 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe87168688190968f7209b660a1a8 completed May 22, 2026, 5:24 a.m.
Created at: April 18, 2026, 2:18 a.m.