Triple

T9440608
Position Surface form Disambiguated ID Type / Status
Subject Coosje van Bruggen E227633 entity
Predicate notableWork P4 FINISHED
Object Saw, Sawing E764321 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: Saw, Sawing | Statement: [Coosje van Bruggen, notableWork, Saw, Sawing]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Saw, Sawing
Context triple: [Coosje van Bruggen, notableWork, Saw, Sawing]
  • A. Saw, Sawing chosen
    "Saw, Sawing" is a large-scale public sculpture by Coosje van Bruggen (in collaboration with Claes Oldenburg) depicting an oversized hand saw emerging from the ground in a characteristically playful, monumental Pop Art style.
  • B. SAW
    SAW is the IATA airport code for Sabiha Gökçen International Airport, a major international airport serving Istanbul, Turkey.
  • C. SawTeen See
    SawTeen See is a prominent structural engineer known for her work on major skyscraper projects and for her long professional and personal partnership with fellow engineer Leslie E. Robertson.
  • D. Saw 3D
    Saw 3D is a 2010 American horror film in the Saw franchise, marketed as the series’ first 3D installment and intended as a concluding chapter to the long-running torture-porn saga.
  • E. Saw
    Saw is a 2004 horror film that launched a popular franchise known for its psychological terror, elaborate death traps, and twist ending.
  • 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_69ca843884488190ad6cbe0153088234 completed March 30, 2026, 2:10 p.m.
NER Named-entity recognition batch_69cd7ee36f908190826994db91b18466 completed April 1, 2026, 8:24 p.m.
NED1 Entity disambiguation (via context triple) batch_69d1105dc6b48190bd6c7d932d9f48d5 completed April 4, 2026, 1:21 p.m.
Created at: March 30, 2026, 7:50 p.m.