Triple

T24161635
Position Surface form Disambiguated ID Type / Status
Subject Serra da Capivara National Park E598854 entity
Predicate locatedNear P294 FINISHED
Object João Costa
João Costa is a municipality in the state of Piauí, Brazil, known for its proximity to the archaeologically significant Serra da Capivara National Park.
E1633760 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: João Costa | Statement: [Serra da Capivara National Park, locatedNear, João Costa]
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: João Costa
Triple: [Serra da Capivara National Park, locatedNear, João Costa]
Generated description
João Costa is a municipality in the state of Piauí, Brazil, known for its proximity to the archaeologically significant Serra da Capivara National Park.

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_69e288cb0a3081909ef221744f274384 completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1e0e9cd6c81908c33242f19fcc034 completed April 29, 2026, 10:43 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe33fb58481909d8e06087fd0508f completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe3f19fec81909b7dd2fd9975336e completed May 22, 2026, 5:04 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe46b72b48190b2c0d2d9ddaf3107 completed May 22, 2026, 5:06 a.m.
Created at: April 17, 2026, 11:32 p.m.