Triple

T8849086
Position Surface form Disambiguated ID Type / Status
Subject Marjorie Acker Phillips E210586 entity
Predicate familyName P18 FINISHED
Object Phillips E71930 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: Phillips | Statement: [Marjorie Acker Phillips, familyName, Phillips]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Phillips
Context triple: [Marjorie Acker Phillips, familyName, Phillips]
  • A. Phillips chosen
    Phillips is a common English-language surname borne by numerous notable individuals across fields such as science, politics, sports, and the arts.
  • B. Philipse
    Philipse is the surname of a prominent colonial-era merchant and landowning family in what is now New York, notably associated with Frederick Philipse I.
  • C. Phillips (company name)
    Phillips is a leading international auction house specializing in contemporary art, design, watches, and other luxury collectibles.
  • D. Filips
    Filips is the given name of Philip William, Prince of Orange, a 16th-century Dutch nobleman and heir to William the Silent.
  • E. Brandt
    Brandt is the obsequious personal assistant to the wealthy Jeffrey Lebowski in the cult film "The Big Lebowski," often serving as a nervous intermediary between him and the Dude.
  • 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_69ca838a424c8190b1ecac115c2927e7 completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cc60aa6db0819097c3257499200afc completed April 1, 2026, 12:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cf89c6788881908d6f5c49434b556d completed April 3, 2026, 9:35 a.m.
Created at: March 30, 2026, 6:49 p.m.