Triple

T6523923
Position Surface form Disambiguated ID Type / Status
Subject Troy Tulowitzki E151254 entity
Predicate givenName P17 FINISHED
Object Troy E436420 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: [Troy Tulowitzki, givenName, Troy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Troy
Context triple: [Troy Tulowitzki, givenName, 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
    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 chosen
    Troy is a masculine given name of ancient origin, famously borne by former NFL quarterback Troy Aikman.
  • 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_69c687f522748190b3058405553cdabd completed March 27, 2026, 1:36 p.m.
NER Named-entity recognition batch_69c6ad970afc81909d3231203eacf413 completed March 27, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c6cb74dfac81908eb44811869450ae completed March 27, 2026, 6:24 p.m.
Created at: March 27, 2026, 1:45 p.m.