Triple

T16622309
Position Surface form Disambiguated ID Type / Status
Subject Diane Salinger E403863 entity
Predicate notableWork P4 FINISHED
Object The American President E90650 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: The American President | Statement: [Diane Salinger, notableWork, The American President]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The American President
Context triple: [Diane Salinger, notableWork, The American President]
  • A. The American President chosen
    The American President is a 1995 romantic comedy-drama film directed by Rob Reiner that follows a widowed U.S. president who falls in love with a lobbyist while navigating the political pressures of the White House.
  • B. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Chamber of Deputies.
  • C. Mr. President
    Mr. President is the formal style of address used for the head of state of Algeria.
  • D. Mr. President
    "Mr. President" is the formal style of address used for the presiding officer of the Massachusetts Senate.
  • E. Mr. President
    "Mr. President" is the formal style of address used for the head of state of the Russian Federation.
  • 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_69d883897eb481909eaaa088ba9918d9 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e3754e80ec8190b3c66b33dbc7463c completed April 18, 2026, 12:13 p.m.
NED1 Entity disambiguation (via context triple) batch_6a007db27f788190a3c57b7ea8a8a9c6 completed May 10, 2026, 12:44 p.m.
Created at: April 10, 2026, 5:17 a.m.