Triple

T10496867
Position Surface form Disambiguated ID Type / Status
Subject Jennifer Carpenter E247560 entity
Predicate familyName P18 FINISHED
Object Carpenter E275002 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: Carpenter | Statement: [Jennifer Carpenter, familyName, Carpenter]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Carpenter
Context triple: [Jennifer Carpenter, familyName, Carpenter]
  • A. Carpenter chosen
    Carpenter is an occupational surname originally referring to someone who works with wood, now borne by many people across English-speaking countries.
  • B. The Carpenter
    The Carpenter is a painting by Dutch Golden Age artist Abraham Bloemaert, exemplifying his detailed and dramatic religious and genre scenes.
  • C. Schrinner
    Schrinner is a German-language surname most notably associated with Australian politician Adrian Schrinner, the Lord Mayor of Brisbane.
  • D. Craftsman
    Craftsman is a well-known American brand of tools, lawn and garden equipment, and workwear recognized for its durability and long association with home improvement and DIY projects.
  • E. Carpender
    Carpender is a surname most notably associated with Arthur S. Carpender, an American naval officer and Medal of Honor recipient.
  • 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_69d381c309b88190af78aa681cf6a4c2 completed April 6, 2026, 9:49 a.m.
NER Named-entity recognition batch_69d5098cd82c8190b44127a66c9c75ae completed April 7, 2026, 1:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69d8dcbafe9481908fb23cfdf150adac completed April 10, 2026, 11:19 a.m.
Created at: April 6, 2026, 12:24 p.m.