Triple

T8519150
Position Surface form Disambiguated ID Type / Status
Subject Clara Martini E201651 entity
Predicate familyName P18 FINISHED
Object Martini E38874 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: Martini | Statement: [Clara Martini, familyName, Martini]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Martini
Context triple: [Clara Martini, familyName, Martini]
  • A. Martini chosen
    Martini is a common Italian surname shared by various notable individuals in fields such as acting, sports, and politics.
  • B. French Martini
    The French Martini is a modern vodka-based cocktail known for its fruity blend of pineapple juice and raspberry liqueur, yielding a smooth, slightly sweet, and elegant drink.
  • C. Caffè Negroni
    Caffè Negroni is a historic Italian café located on Turin’s elegant Piazza San Carlo, known for its traditional atmosphere and classic drinks.
  • D. Champagne Cocktail
    A Champagne Cocktail is a classic sparkling wine drink typically made by soaking a sugar cube with bitters, topping it with chilled Champagne, and garnishing with a citrus twist.
  • E. Martini & Rossi
    Martini & Rossi is an Italian company best known for producing vermouth and sparkling wines, as well as for its iconic Martini Racing motorsport sponsorships.
  • 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe627de908190b463da0f26da4ffb completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69ce88ec84208190ab72c8411e6cc4c2 completed April 2, 2026, 3:19 p.m.
Created at: March 30, 2026, 6:16 p.m.