Triple

T5532875
Position Surface form Disambiguated ID Type / Status
Subject Enter Nowhere E145089 entity
Predicate hasCharacter P2308 FINISHED
Object Tom E128299 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: Tom | Statement: [Enter Nowhere, hasCharacter, Tom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom
Context triple: [Enter Nowhere, hasCharacter, Tom]
  • A. Tom chosen
    Tom is a common masculine given name, often used in English-speaking countries as a short form of Thomas.
  • B. TOM
    TOM is the ICAO airline designator used to identify TUI Airways in international aviation operations.
  • C. Tim
    Tim is the given name of Tim Wu, a prominent legal scholar and policy advocate known for coining the term "net neutrality."
  • D. Tony
    Tony is one of the central protagonists in Margaret Atwood’s novel "The Robber Bride," known for her intellectual, introspective nature and complex relationships with the other main characters.
  • E. Tony
    Tony is a central, shape-shifting conman character in the fantasy film "The Imaginarium of Doctor Parnassus," notably portrayed by multiple actors including Heath Ledger, Johnny Depp, Jude Law, and Colin Farrell.
  • 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_69c008f9955881909bfa8348b56b4739 completed March 22, 2026, 3:21 p.m.
NER Named-entity recognition batch_69c01f9ea2c88190a68642f5799bd8ff completed March 22, 2026, 4:58 p.m.
NED1 Entity disambiguation (via context triple) batch_69c0280cb42c8190bf5ba546aca5edce completed March 22, 2026, 5:34 p.m.
Created at: March 22, 2026, 3:34 p.m.