Triple

T7402895
Position Surface form Disambiguated ID Type / Status
Subject Mon Paris E170790 entity
Predicate hasFlanker P39620 FINISHED
Object Mon Paris Floral E170790 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: Mon Paris Floral | Statement: [Mon Paris, hasFlanker, Mon Paris Floral]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Mon Paris Floral
Context triple: [Mon Paris, hasFlanker, Mon Paris Floral]
  • A. Mille Fleurs
    Mille Fleurs is a historic estate residence located within the Sands Point Preserve on Long Island’s North Shore.
  • B. Marché aux Fleurs
    Marché aux Fleurs is a famous open-air flower market in Nice, France, known for its colorful stalls and traditional Provençal atmosphere.
  • C. Sunflowers (Paris series)
    Sunflowers (Paris series) is a group of still-life paintings of sunflowers by Vincent van Gogh created in Paris in 1887, preceding his more famous Arles sunflower series.
  • D. Mon Paris chosen
    Mon Paris is a modern, fruity-floral women’s fragrance by Yves Saint Laurent Beauté known for its sweet, sensual scent and chic, contemporary Parisian style.
  • E. City of Flowers
    City of Flowers is a popular nickname for Zamboanga City in the Philippines, highlighting its abundance of vibrant flora and garden-like landscapes.
  • 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_69c68a6010108190925e5284de022660 completed March 27, 2026, 1:47 p.m.
NER Named-entity recognition batch_69c6f26ea27c8190a55e0e0314b463d8 completed March 27, 2026, 9:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69c81110d7648190a8938db7061be454 completed March 28, 2026, 5:34 p.m.
Created at: March 27, 2026, 3:10 p.m.