Triple

T3699706
Position Surface form Disambiguated ID Type / Status
Subject Lipstick Building E78546 entity
Predicate nickname P55 FINISHED
Object Lipstick Building E78546 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: Lipstick Building | Statement: [Lipstick Building, nickname, Lipstick Building]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Lipstick Building
Context triple: [Lipstick Building, nickname, Lipstick Building]
  • A. Lipstick Building chosen
    The Lipstick Building is a distinctive postmodern office skyscraper in Midtown Manhattan, New York City, known for its elliptical, tiered form that resembles a tube of lipstick.
  • B. Lipstick Jungle
    Lipstick Jungle is an American comedy-drama television series that follows the professional and personal lives of three powerful women navigating careers and relationships in New York City.
  • C. Red Lips
    "Red Lips" is a 2012 electropop/grunge-influenced single by American singer Sky Ferreira, known for its abrasive sound and collaboration with producer Greg Kurstin.
  • D. LIP
    LIP is the vehicle registration code for the town of Blomberg in the Lippe district of North Rhine-Westphalia, Germany.
  • E. Glitz
    Glitz is a crime novel by Elmore Leonard that follows a tough Miami cop entangled with a vengeful ex-con and the seedy underworld of Atlantic City.
  • 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_69ad85e3b1888190abc983e06968696d completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adc513d26c8190bfdf25f62af8c6ca completed March 8, 2026, 6:50 p.m.
NED1 Entity disambiguation (via context triple) batch_69b4c3df86bc819088db92eecee69fd3 completed March 14, 2026, 2:11 a.m.
Created at: March 8, 2026, 3:26 p.m.