Triple

T15355039
Position Surface form Disambiguated ID Type / Status
Subject Jennifer Aniston E367150 entity
Predicate givenName P17 FINISHED
Object Jennifer E47548 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: Jennifer | Statement: [Jennifer Aniston, givenName, Jennifer]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jennifer
Context triple: [Jennifer Aniston, givenName, Jennifer]
  • A. Jennifer chosen
    Jennifer is a common feminine given name of English origin, derived from the Cornish form of Guinevere and widely used in many English-speaking countries.
  • B. Jennifer
    "Jennifer" is the viral R&B-pop single by American singer Trinidad Cardona that gained widespread attention online and launched his music career.
  • C. Jane
    Jane is a feminine given name of English origin that has been widely used in many English-speaking countries for centuries.
  • D. Jane
    Jane was a British sealing and exploration vessel commanded by James Weddell during his early 19th-century Antarctic voyages.
  • E. Jane
    Jane is a powerful vampire in the Twilight series, known for her childlike appearance and her ability to inflict excruciating pain with her mind as a high-ranking enforcer of the Volturi.
  • 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_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e2c00648190ae2325e1ee58dcfd completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff02012fa48190a108f1ca710ffb15 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:18 a.m.