Triple

T6438157
Position Surface form Disambiguated ID Type / Status
Subject Jacob’s Folly E129949 entity
Predicate hasCharacter P2308 FINISHED
Object Masha unclear NED1 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: Masha | Statement: [Jacob’s Folly, hasCharacter, Masha]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Masha
Context triple: [Jacob’s Folly, hasCharacter, Masha]
  • A. Masha
    Masha is a diminutive and affectionate Russian form of the given name Mary (Maria).
  • B. Malvina
    Malvina is a feminine given name of Scottish origin, often associated with literary and romantic traditions.
  • C. Misha
    Misha is the bear mascot of the 1980 Moscow Summer Olympics, widely remembered for its iconic, sentimental farewell during the closing ceremony.
  • D. Mila
    Mila is a leading artificial intelligence research institute based in Quebec, renowned for its work in deep learning and machine learning.
  • E. Grushenka
    Grushenka is a central female character in Fyodor Dostoevsky's novel "The Brothers Karamazov," known for her complex mix of sensuality, capriciousness, and capacity for moral and spiritual transformation.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69c0084caac48190a7bc2ad8ba44536f completed March 22, 2026, 3:18 p.m.
NER Named-entity recognition batch_69c06965a5d48190a5860da9e22dc6e0 completed March 22, 2026, 10:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69c640f56ee881909f7b7f0909e1d701 completed March 27, 2026, 8:33 a.m.
Created at: March 22, 2026, 4:45 p.m.