Triple

T2695570
Position Surface form Disambiguated ID Type / Status
Subject Troilus and Criseyde E58502 entity
Predicate settingLocation P40 FINISHED
Object Troy E112533 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 | Statement: [Troilus and Criseyde, settingLocation, Troy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troy
Context triple: [Troilus and Criseyde, settingLocation, Troy]
  • A. Troy
    Troy is a small city in southeastern Alabama known for being the home of Troy University and its vibrant college-town atmosphere.
  • B. Troy
    Troy is a historic city in eastern New York State, known for its 19th-century architecture and role in the Industrial Revolution as a major manufacturing center.
  • C. Troy
    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 chosen
    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_69ab4ac269e481909cb317d79e68b75b completed March 6, 2026, 9:44 p.m.
NER Named-entity recognition batch_69abda2f7bf88190a1e3103dd014d871 completed March 7, 2026, 7:56 a.m.
NED1 Entity disambiguation (via context triple) batch_69afaf6aa78c8190b57be36042008361 completed March 10, 2026, 5:43 a.m.
Created at: March 6, 2026, 9:55 p.m.