Triple

T14910601
Position Surface form Disambiguated ID Type / Status
Subject Tammy Suzanne Green Baldwin E371250 entity
Predicate givenName P17 FINISHED
Object Tammy E732794 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: Tammy | Statement: [Tammy Suzanne Green Baldwin, givenName, Tammy]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Tammy
Context triple: [Tammy Suzanne Green Baldwin, givenName, Tammy]
  • A. Tammy
    Tammy is a resourceful, quirky suburban mom-turned-criminal and a key member of the heist crew in the film "Ocean's 8," portrayed by Sarah Paulson.
  • B. Tammy
    "Tammy" is a popular 1957 ballad closely associated with the film "Tammy and the Bachelor" and widely remembered for its romantic, nostalgic melody.
  • C. Tammy
    Tammy is one of Madea’s outspoken, short-tempered daughters in Tyler Perry’s "Madea’s Big Happy Family," known for her combative attitude and family conflicts.
  • D. Tammy chosen
    Tammy is a feminine given name commonly used in English-speaking countries, often as a diminutive of names like Tamara or Tamsin.
  • E. Tammy
    "Tammy" is a 2014 American comedy film starring Melissa McCarthy as a down-on-her-luck woman who embarks on a chaotic road trip with her grandmother.
  • 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_69d85cc7ea3481908228b5acb7d06f12 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69ded61c6b9c8190a92934d49b98fe46 completed April 15, 2026, 12:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69fe72bb366481909706d511f5ae1290 completed May 8, 2026, 11:33 p.m.
Created at: April 10, 2026, 2:26 a.m.