Triple

T11020581
Position Surface form Disambiguated ID Type / Status
Subject Gaspar Noé E260475 entity
Predicate directed P7373 FINISHED
Object Seul contre tous E900257 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: Seul contre tous | Statement: [Gaspar Noé, directed, Seul contre tous]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Seul contre tous
Context triple: [Gaspar Noé, directed, Seul contre tous]
  • A. Seul contre tous chosen
    Seul contre tous is a bleak and provocative French drama film by Gaspar Noé that follows a morally decaying butcher spiraling into violence and despair.
  • B. Seoul Special City
    Seoul Special City is the capital and largest metropolis of South Korea, serving as the country’s political, economic, and cultural center.
  • C. Les Rivalités
    Les Rivalités is a section of Honoré de Balzac’s multi-part novel cycle Scènes de la vie de province, depicting the social tensions and conflicts within provincial French society.
  • D. Saarang
    Saarang is the annual cultural festival of IIT Madras, known as one of India’s largest and most prominent college cultural fests featuring music, arts, literary, and performing arts events.
  • E. Mr. Sunshine
    Mr. Sunshine is a television comedy series in which actor Nate Torrence played a notable role.
  • 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_69d6aa9687448190b28d353b1b6a610e completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d797baad408190a53fd6941a750f68 completed April 9, 2026, 12:12 p.m.
NED1 Entity disambiguation (via context triple) batch_69e3a98725808190903639866a3e745f completed April 18, 2026, 3:55 p.m.
Created at: April 8, 2026, 9:25 p.m.