Triple

T20525762
Position Surface form Disambiguated ID Type / Status
Subject Eric Ambler E503930 entity
Predicate notableWork P4 FINISHED
Object State of Siege NE NERFINISHED

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: State of Siege | Statement: [Eric Ambler, notableWork, State of Siege]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: State of Siege
Context triple: [Eric Ambler, notableWork, State of Siege]
  • A. State of Siege
    "State of Siege" is a long poem by Palestinian poet Mahmoud Darwish that reflects on life under military occupation, blending personal meditation with political and existential themes.
  • B. State of Siege chosen
    State of Siege is a 1972 political thriller film by Costa-Gavras that dramatizes the kidnapping of a U.S. official in Uruguay to critique American involvement in Latin American politics.
  • C. Lang Siege
    Lang Siege is an alternative name for the Marian civil war, a 16th-century Scottish conflict over the legitimacy of Mary, Queen of Scots’ rule.
  • D. Under Siege
    Under Siege is a recurring professional wrestling event produced by the American promotion Impact Wrestling.
  • E. Under Siege
    Under Siege is a 1992 action thriller film starring Steven Seagal as a former Navy SEAL battling terrorists aboard a U.S. battleship.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (2 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_69e0b4b3a6e08190ae663701f50fab8e completed April 16, 2026, 10:06 a.m.
NER Named-entity recognition batch_69e6a06504b48190b3f1defdc23a47d5 completed April 20, 2026, 9:53 p.m.
Created at: April 16, 2026, 11:37 a.m.