Triple

T12219829
Position Surface form Disambiguated ID Type / Status
Subject Tom Kempinski E291183 entity
Predicate givenName P17 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: [Tom Kempinski, givenName, Tom]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tom
Context triple: [Tom Kempinski, givenName, 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. TOM
    TOM is the National Rail station code assigned to Tottenham Hale railway station in London, England.
  • D. Tim
    Tim is a fictional character from Robert Silverberg’s science fiction novel "The Book of Skulls," one of the four college students who seek an ancient order promising immortality at a terrible price.
  • E. Tim
    Tim is a common masculine given name used in many English-speaking countries, often as a short form of Timothy.
  • 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_69d6ab668acc8190963ba424049d6aee completed April 8, 2026, 7:24 p.m.
NER Named-entity recognition batch_69d91c951f5881908db6edfda1153d6f completed April 10, 2026, 3:51 p.m.
NED1 Entity disambiguation (via context triple) batch_69f60aa4f4388190a787dde12190c51a completed May 2, 2026, 2:31 p.m.
Created at: April 8, 2026, 9:51 p.m.