Triple

T7524712
Position Surface form Disambiguated ID Type / Status
Subject Adrianne Palicki E177861 entity
Predicate familyName P18 FINISHED
Object Palicki E177861 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: Palicki | Statement: [Adrianne Palicki, familyName, Palicki]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Palicki
Context triple: [Adrianne Palicki, familyName, Palicki]
  • A. Palicki chosen
    Palicki is a surname most notably associated with American actress Adrianne Palicki, known for her roles in television and film.
  • B. Pankiewicz
    Pankiewicz is a Polish surname most notably associated with Tadeusz Pankiewicz, the pharmacist who ran the “Under the Eagle” pharmacy in the Kraków Ghetto during World War II.
  • C. Witos
    Witos is a Polish surname most notably borne by Wincenty Witos, a prominent early 20th-century Polish politician and three-time Prime Minister.
  • D. Piekarski
    Piekarski is a Polish surname, typically derived from occupational or locational roots, borne by various individuals of Polish origin.
  • E. Radkiewicz
    Radkiewicz is a Polish surname most notably associated with Stanisław Radkiewicz, a prominent communist-era politician and security official in Poland.
  • 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_69c69f29bf3081909a146aec7755f185 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f7c61b508190b582f54ecbb387e3 completed March 27, 2026, 9:33 p.m.
NED1 Entity disambiguation (via context triple) batch_69c84631e6bc819099b3a7819c3ae9a7 completed March 28, 2026, 9:20 p.m.
Created at: March 27, 2026, 3:46 p.m.