Triple

T15544758
Position Surface form Disambiguated ID Type / Status
Subject Cámara (Argentine Navy officer) E370574 entity
Predicate namedAfterBy P63 FINISHED
Object Cámara Base E1101587 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: Cámara Base | Statement: [Cámara (Argentine Navy officer), namedAfterBy, Cámara Base]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Cámara Base
Context triple: [Cámara (Argentine Navy officer), namedAfterBy, Cámara Base]
  • A. Cámara Base
    Cámara Base is an Argentine research station in Antarctica that operates primarily during the austral summer to support scientific and logistical activities in the region.
  • B. The Camera
    The Camera is a seminal photography book by Ansel Adams that explores the technical and artistic use of cameras in creating expressive photographs.
  • C. Caméra One
    Caméra One is a French film production company known for producing acclaimed art-house and auteur-driven movies.
  • D. Teniente Cámara Base chosen
    Teniente Cámara Base is an Argentine Antarctic research station that supports scientific studies and maintains Argentina’s presence in the Antarctic region.
  • E. Camira
    Camira is a compact family car model produced by Holden, the Australian subsidiary of General Motors, during the 1980s.
  • 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_69d85cc521a08190921fb50319dddc34 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e0443410408190a249889edcd9c599 completed April 16, 2026, 2:06 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff455a38188190a593c70be09d6103 completed May 9, 2026, 2:31 p.m.
Created at: April 10, 2026, 4:07 a.m.