Triple

T15353620
Position Surface form Disambiguated ID Type / Status
Subject Michael Peyser E367115 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: [Michael Peyser, notableWork, The American President]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: The American President
Context triple: [Michael Peyser, 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_69d85a1355608190a6673ddb67231d54 completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e2a8e88819093e4b7479b2c80cd completed April 16, 2026, 1:40 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff01ff42d48190897e6653d2b4f8a4 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:18 a.m.