Triple

T15673228
Position Surface form Disambiguated ID Type / Status
Subject Paris (Orlando Bloom) E377371 entity
Predicate appearsIn P795 FINISHED
Object Troy (2004 film) E77827 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: Troy (2004 film) | Statement: [Paris (Orlando Bloom), appearsIn, Troy (2004 film)]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troy (2004 film)
Context triple: [Paris (Orlando Bloom), appearsIn, Troy (2004 film)]
  • A. Troy
    "Troy" is a powerful early single by Irish singer-songwriter Sinéad O’Connor, known for its intense emotional delivery and poetic lyrics.
  • B. Troy
    Troy is a small city in southeastern Alabama known for being the home of Troy University and its vibrant college-town atmosphere.
  • C. Troy chosen
    Troy is a 2004 epic historical war film loosely based on Homer's Iliad, depicting the legendary conflict between the Greeks and Trojans.
  • D. Troy
    Troy is the legendary ancient city in Asia Minor that was the focal point of the Trojan War in Greek and Roman mythology.
  • E. Troy
    Troy is a suburban city in Michigan known for its strong business community, shopping centers, and role as a key part of the Detroit metropolitan area.
  • 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_69d85cd2e28481909d4e975bee20872f completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04f2c996c8190a9ebe0e92608feaa completed April 16, 2026, 2:53 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff6edb12bc8190b2c5558190671ae5 completed May 9, 2026, 5:28 p.m.
Created at: April 10, 2026, 4:16 a.m.