Triple

T3066666
Position Surface form Disambiguated ID Type / Status
Subject Quills E62118 entity
Predicate stars P1956 FINISHED
Object Joaquin Phoenix E68750 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: Joaquin Phoenix | Statement: [Quills, stars, Joaquin Phoenix]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Joaquin Phoenix
Context triple: [Quills, stars, Joaquin Phoenix]
  • A. Joaquin Phoenix chosen
    Joaquin Phoenix is an acclaimed American actor known for his intense, transformative performances in films such as "Joker," "Walk the Line," and "The Master."
  • B. Benicio del Toro
    Benicio del Toro is an acclaimed Puerto Rican actor known for his intense, brooding performances in films such as "Traffic," "The Usual Suspects," and "Sicario."
  • C. Philip Seymour Hoffman
    Philip Seymour Hoffman was an acclaimed American actor known for his intense, character-driven performances in films such as "Capote," "The Master," and "Synecdoche, New York."
  • D. Casey Affleck
    Casey Affleck is an American actor and filmmaker known for his understated, emotionally intense performances in films such as "Manchester by the Sea," for which he won the Academy Award for Best Actor.
  • E. James Franco
    James Franco is an American actor, filmmaker, and academic known for his diverse roles in films like "127 Hours" and "Pineapple Express" and for his often experimental approach to art and performance.
  • 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_69ad85793e5c8190a358049bc4a98d8c completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada0fd87308190918e7b616f033faa completed March 8, 2026, 4:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69b1ef16cf2881908265dfe8a1e3424d completed March 11, 2026, 10:39 p.m.
Created at: March 8, 2026, 3:02 p.m.