Triple

T17018019
Position Surface form Disambiguated ID Type / Status
Subject The International E412870 entity
Predicate castMember P1668 FINISHED
Object Patrick Baladi E708437 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: Patrick Baladi | Statement: [The International, castMember, Patrick Baladi]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Patrick Baladi
Context triple: [The International, castMember, Patrick Baladi]
  • A. Patrick Baladi chosen
    Patrick Baladi is a British actor best known for his television roles in series such as The Office (UK), Mistresses, and Line of Duty.
  • B. Anthony Pelissier
    Anthony Pelissier was a British actor, screenwriter, and film director known for his work in mid-20th-century British cinema, including contributions to Ealing Studios.
  • C. Pierre Azaria
    Pierre Azaria was a French entrepreneur best known for founding the telecommunications company Alcatel.
  • D. Antoine Nahas
    Antoine Nahas was a Lebanese architect best known for designing the National Museum of Beirut, a landmark institution of Lebanon’s cultural heritage.
  • E. Michel Elie
    Michel Elie is a French computer scientist known for his pioneering role in the development of early packet-switching networks, notably through his work on the CYCLADES project.
  • 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_69d886cc4170819093deddc7b8b4b6a7 completed April 10, 2026, 5:12 a.m.
NER Named-entity recognition batch_69e3d480a58c8190a3912d26debb4311 completed April 18, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_6a011b4d6cb881909b64b4368fd97fa9 completed May 10, 2026, 11:57 p.m.
Created at: April 10, 2026, 5:33 a.m.