Triple

T804476
Position Surface form Disambiguated ID Type / Status
Subject Rosa Parks E17197 entity
Predicate familyName P18 FINISHED
Object Parks E73846 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: Parks | Statement: [Rosa Parks, familyName, Parks]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Parks
Context triple: [Rosa Parks, familyName, Parks]
  • A. Parks chosen
    Parks is a common English-language surname borne by numerous notable individuals across fields such as politics, civil rights, sports, and the arts.
  • B. Metro Parks and Nature
    Metro Parks and Nature is the regional government agency for the Portland, Oregon metropolitan area that manages parks, natural areas, and recreational facilities, including the Oregon Zoo.
  • C. Namba Parks
    Namba Parks is a large multi-level shopping, dining, and entertainment complex in Osaka, Japan, known for its distinctive rooftop garden and canyon-like architectural design.
  • D. Home Park
    Home Park is a historic royal deer park and landscaped estate surrounding Windsor Castle in Berkshire, England.
  • E. Paseo del Bosque park
    Paseo del Bosque park is a large urban green space in La Plata, Argentina, known for its wooded areas, recreational facilities, and cultural attractions.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 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_69a49378b9c48190adbf5f62e5b7aca1 completed March 1, 2026, 7:28 p.m.
NER Named-entity recognition batch_69a4aabebff08190880e4876ff58bcfe completed March 1, 2026, 9:08 p.m.
NED1 Entity disambiguation (via context triple) batch_69a68926c04081908923a7d114d1842d completed March 3, 2026, 7:09 a.m.
Created at: March 1, 2026, 7:38 p.m.