Triple

T8258299
Position Surface form Disambiguated ID Type / Status
Subject Maya E193124 entity
Predicate hasVariant P455 FINISHED
Object Maja E448720 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: Maja | Statement: [Maya, hasVariant, Maja]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Maja
Context triple: [Maya, hasVariant, Maja]
  • A. Maja chosen
    Maja was the younger sister of physicist Albert Einstein, known for her close relationship with him and her background in literature and languages.
  • B. Marga
    Marga is a feminine given name, commonly used as a short or diminutive form of names like Margarita or Margareta.
  • C. Majkin
    Majkin is a small settlement located on Namu Atoll in the Marshall Islands, likely serving as one of the atoll’s primary residential communities.
  • D. Lujza
    Lujza is a given name, primarily used in Central and Eastern Europe, that corresponds to the name Luisa or Louise in other languages.
  • E. Maja e Lubotenit
    Maja e Lubotenit is a prominent peak in the Šar Mountains on the border of Kosovo and North Macedonia, known for its scenic alpine landscapes and popular hiking routes.
  • 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_69ca82dfad9c8190b8cd18fb89f50f40 completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb78fce9308190ac36512e80b06b52 completed March 31, 2026, 7:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd355bef508190894bd01ec39e83f6 completed April 1, 2026, 3:10 p.m.
Created at: March 30, 2026, 5:49 p.m.