Triple

T14508455
Position Surface form Disambiguated ID Type / Status
Subject THINKFilm E340329 entity
Predicate distributed P8091 FINISHED
Object The Bridge E768580 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: The Bridge | Statement: [THINKFilm, distributed, The Bridge]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The Bridge
Context triple: [THINKFilm, distributed, The Bridge]
  • A. The Bridge
    The Bridge is an American crime drama television series in which Diane Kruger stars as a brilliant but socially awkward detective investigating cross-border murders on the U.S.–Mexico frontier.
  • B. The Bridge
    The Bridge is the English translation of "Die Brücke," the name of the influential early 20th-century German Expressionist artist group.
  • C. The Bridge
    The Bridge is an ambitious modernist epic poem by Hart Crane that reimagines American history and experience through the symbolic central image of the Brooklyn Bridge.
  • D. The Bridge
    "The Bridge" is a musical track from the score of the animated film *Kung Fu Panda* (2008), composed by Hans Zimmer and John Powell.
  • E. The Bridge chosen
    The Bridge is a film or television work featuring German actress Franka Potente, known for her intense and dynamic performances.
  • 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_69d822d9c0408190b9a2b3643e58bb4d completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69de94e40e44819084f323f8f9982b75 completed April 14, 2026, 7:26 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd6da26a308190bf86ed1edbe8d57e completed May 8, 2026, 4:59 a.m.
Created at: April 10, 2026, 1:21 a.m.