Triple

T3168756
Position Surface form Disambiguated ID Type / Status
Subject How Green Was My Valley E66275 entity
Predicate castMember P1668 FINISHED
Object Sara Allgood E346154 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: Sara Allgood | Statement: [How Green Was My Valley, castMember, Sara Allgood]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Sara Allgood
Context triple: [How Green Was My Valley, castMember, Sara Allgood]
  • A. Sara Allgood chosen
    Sara Allgood was an Irish stage and film actress known for her character roles in early 20th-century theatre and classic Hollywood cinema.
  • B. Sara Henry
    Sara Henry is known as the wife of American voice actor and comedian Mike Henry, recognized for his work on shows like Family Guy.
  • C. Sara Haden
    Sara Haden was an American character actress best known for her supporting roles in classic Hollywood films of the 1930s and 1940s, including several entries in the Andy Hardy series.
  • D. Susan Allerton
    Susan Allerton was a member of the Allerton family associated with early colonial New England, known primarily as a sibling of Mayflower passenger Isaac Allerton.
  • E. Elizabeth Reaser
    Elizabeth Reaser is an American actress best known for her roles in the Twilight film series and the television drama Grey's Anatomy.
  • 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_69ad8585d7988190af37365331093ccd completed March 8, 2026, 2:19 p.m.
NER Named-entity recognition batch_69ada64726048190933dbdc44258703e completed March 8, 2026, 4:39 p.m.
NED1 Entity disambiguation (via context triple) batch_69b31a6206988190a6aaecbfe8ccf0bf completed March 12, 2026, 7:56 p.m.
Created at: March 8, 2026, 3:06 p.m.