Triple

T7595203
Position Surface form Disambiguated ID Type / Status
Subject Flash Gordon E179840 entity
Predicate character P662 FINISHED
Object Dr. Hans Zarkov E410034 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: Dr. Hans Zarkov | Statement: [Flash Gordon, character, Dr. Hans Zarkov]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Dr. Hans Zarkov
Context triple: [Flash Gordon, character, Dr. Hans Zarkov]
  • A. Dr. Hans Zarkov chosen
    Dr. Hans Zarkov is a brilliant but eccentric scientist and ally of Flash Gordon in the classic science fiction adventure series.
  • B. Max Zorin
    Max Zorin is the main villain in the James Bond film "A View to a Kill," a ruthless industrialist plotting to destroy Silicon Valley for financial gain.
  • C. Dr. Petrov
    Dr. Petrov is a minor Soviet medical officer aboard the submarine Red October in Tom Clancy’s Cold War thriller "The Hunt for Red October."
  • D. Dr. Martin Brenner
    Dr. Martin Brenner is a central antagonist in the TV series "Stranger Things," a cold and manipulative scientist who leads secret government experiments on children with psychic abilities.
  • E. Dr. Werner Klopek
    Dr. Werner Klopek is the mysterious and unsettling neighbor suspected of dark secrets in the dark comedy film "The 'Burbs."
  • 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_69c69f3487ec8190bf7acdf2dd91e6d6 completed March 27, 2026, 3:16 p.m.
NER Named-entity recognition batch_69c6f9bbcd8081909a229d7faa2ffdc8 completed March 27, 2026, 9:42 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8619d6f2081908c8b589d4106691f completed March 28, 2026, 11:17 p.m.
Created at: March 27, 2026, 3:53 p.m.