Triple

T16890780
Position Surface form Disambiguated ID Type / Status
Subject Jerry Reed E424164 entity
Predicate givenName P17 FINISHED
Object Jerry E486416 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: Jerry | Statement: [Jerry Reed, givenName, Jerry]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Jerry
Context triple: [Jerry Reed, givenName, Jerry]
  • A. Jerry
    Jerry is one of the two cross-dressing musician protagonists in the classic 1959 comedy film "Some Like It Hot," famously portrayed by Jack Lemmon.
  • B. Jerry
    Jerry is the troubled, isolated protagonist of Edward Albee’s one-act play "The Zoo Story," whose intense encounter with a stranger on a park bench drives the drama’s exploration of alienation and human connection.
  • C. Jerry
    Jerry is the given name of Jerry Lee Lewis, the influential American rock and roll and country music singer and pianist known for hits like "Great Balls of Fire."
  • D. Jerry chosen
    Jerry is a masculine given name commonly used in English-speaking countries, often as a diminutive of names like Gerald, Jerome, or Jeremy.
  • E. Jerry
    Jerry is the video store clerk protagonist of the comedy film "Be Kind Rewind," known for recreating erased movies with homemade, low-budget remakes.
  • 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_69d889da3e8c8190a2b118f383f0beac completed April 10, 2026, 5:25 a.m.
NER Named-entity recognition batch_69e3bbc473d4819090cfea374ef5ca49 completed April 18, 2026, 5:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a00c7a7fd8481908ef82a13418b1c2d completed May 10, 2026, 6 p.m.
Created at: April 10, 2026, 5:29 a.m.