Triple

T5527302
Position Surface form Disambiguated ID Type / Status
Subject Merian C. Cooper E144950 entity
Predicate givenName P17 FINISHED
Object Merian E144950 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: Merian | Statement: [Merian C. Cooper, givenName, Merian]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Merian
Context triple: [Merian C. Cooper, givenName, Merian]
  • A. Merian chosen
    Merian is a given name most notably borne by Merian C. Cooper, the American filmmaker and co-creator of the classic movie "King Kong."
  • B. Wilhelma
    Wilhelma is a renowned zoological and botanical garden in Stuttgart, Germany, known for its extensive animal and plant collections and historic Moorish-style architecture.
  • C. Rineke
    Rineke is a Dutch photographer renowned for her intimate, large-scale portraits that explore identity, vulnerability, and the passage of time.
  • D. Seba
    Seba is a common short form or nickname for the given name Sebastián, frequently used in Spanish-speaking countries.
  • E. Heinsius
    Heinsius is a Dutch surname most notably associated with Anthonie Heinsius, a prominent statesman of the Dutch Republic in the late 17th and early 18th centuries.
  • 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_69c008f873a481909b4d9f7e2db3c37d completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f8a34a48190bcbd0036f79246a9 completed March 22, 2026, 4:57 p.m.
NED1 Entity disambiguation (via context triple) batch_69c027fe1c508190b95b7b5bda96a32d completed March 22, 2026, 5:33 p.m.
Created at: March 22, 2026, 3:34 p.m.