Triple

T10887018
Position Surface form Disambiguated ID Type / Status
Subject Neo Rauch E257073 entity
Predicate notableWork P4 FINISHED
Object “Die Stickerinnen” E891430 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: “Die Stickerinnen” | Statement: [Neo Rauch, notableWork, “Die Stickerinnen”]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: “Die Stickerinnen”
Context triple: [Neo Rauch, notableWork, “Die Stickerinnen”]
  • A. “Die Stickerin” chosen
    “Die Stickerin” is a painting by contemporary German artist Neo Rauch, reflecting his characteristic blend of figurative imagery, surreal narratives, and socialist realist aesthetics.
  • B. Super Stickers
    Super Stickers are animated, paid digital stickers that viewers can purchase during YouTube live streams and Premieres to support creators and stand out in chat.
  • C. Stikker
    Stikker is a surname most notably associated with Dirk Stikker, a Dutch politician and diplomat who served as NATO Secretary General.
  • D. Stickies
    Stickies is the nickname for the Official Irish Republican movement, a left-wing Irish republican organization that emerged from a split in the IRA in the late 1960s.
  • E. Stickies
    Stickies is a simple note-taking application for macOS that lets users create and manage virtual sticky notes on their desktop.
  • 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_69d6aa848804819081b2713ca0bedf06 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d751dea1a88190b916879be8d74413 completed April 9, 2026, 7:14 a.m.
NED1 Entity disambiguation (via context triple) batch_69e154e49ab08190b522b5361ac65c01 completed April 16, 2026, 9:30 p.m.
Created at: April 8, 2026, 9:21 p.m.