Triple

T16492152
Position Surface form Disambiguated ID Type / Status
Subject Mr. President E400592 entity
Predicate relatedConcept P37 FINISHED
Object Madam President unclear NED1 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: Madam President | Statement: [Mr. President, relatedConcept, Madam President]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Madam President
Context triple: [Mr. President, relatedConcept, Madam President]
  • A. Madam President
    Madam President is the formal style of address used for a female head of state serving as President of Romania.
  • B. Madam President
    Madam President is an honorific title used for a female head of state or government, notably associated with Indonesia’s former president Megawati Sukarnoputri.
  • C. Madam President
    "Madam President" is the formal style of address used for a woman serving as President of the Swiss Confederation.
  • D. Madam President
    Madam President is the formal title used for Seraphina Picquery, the witch who serves as President of the Magical Congress of the United States of America in the Harry Potter universe.
  • E. Madam President
    "Madam President" is the formal honorific used to address a woman serving as the presiding officer of the Florida Senate.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide. chosen

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_69d883813098819084f5409539723b59 completed April 10, 2026, 4:58 a.m.
NER Named-entity recognition batch_69e32e30cb648190a52cb32896c4ac5a completed April 18, 2026, 7:09 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0067a168c081908f630b45bf85d9f6 completed May 10, 2026, 11:10 a.m.
Created at: April 10, 2026, 5:13 a.m.