Triple

T14338790
Position Surface form Disambiguated ID Type / Status
Subject Philips E355536 entity
Predicate variantOf P4680 FINISHED
Object Philipps E820613 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: Philipps | Statement: [Philips, variantOf, Philipps]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Philipps
Context triple: [Philips, variantOf, Philipps]
  • A. Philipps chosen
    Philipps is the surname of American actress and television host Busy Philipps, known for roles in series like "Freaks and Geeks" and "Dawson's Creek."
  • B. Phillippe
    Phillippe is a given name and surname, typically a French-influenced variant of Philip, used for both real and fictional individuals.
  • C. Philipp
    Philipp is a male given name of Greek origin, commonly used in various European countries and historically borne by numerous nobles and royals.
  • D. Philipp
    Philipp is the German given name of Philip Melanchthon, the influential 16th-century German Lutheran reformer and collaborator of Martin Luther.
  • E. Philipp
    Philipp was the given name of the 19th-century German botanist and explorer Carl Friedrich Philipp von Martius, renowned for his extensive studies of Brazilian flora.
  • 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_69d8278fa2108190bc0d0e7939c1eb03 completed April 9, 2026, 10:26 p.m.
NER Named-entity recognition batch_69de8e8674c0819091dfbe9c50778c5e completed April 14, 2026, 6:59 p.m.
NED1 Entity disambiguation (via context triple) batch_69fd469bc538819099ed5b7061cf140d completed May 8, 2026, 2:12 a.m.
Created at: April 10, 2026, 1:14 a.m.