Triple

T10068547
Position Surface form Disambiguated ID Type / Status
Subject Siemens NX E213158 entity
Predicate supportsStandard P1587 FINISHED
Object JT E758487 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: JT | Statement: [Siemens NX, supportsStandard, JT]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: JT
Context triple: [Siemens NX, supportsStandard, JT]
  • A. JT
    JT is a 1977 studio album by American singer-songwriter James Taylor that marked his commercial resurgence with hits like "Handy Man" and "Your Smiling Face."
  • B. JT chosen
    JT is a lightweight 3D visualization and data exchange file format commonly used in CAD and PLM workflows for efficient sharing of complex product models.
  • C. JK
    JK is the widely used nickname of Juscelino Kubitschek, the former president of Brazil best known for founding Brasília and promoting rapid national development.
  • D. JR
    JR is a French street artist and photographer renowned for his large-scale public art installations that transform urban spaces and address social and political issues worldwide.
  • E. JR
    JR is a character from Alison Bechdel’s long-running comic strip "Dykes to Watch Out For," which chronicles the lives and relationships of a diverse group of lesbian friends.
  • 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_69ca83977128819084084eb7d1d8c52a completed March 30, 2026, 2:07 p.m.
NER Named-entity recognition batch_69cdcff8d9c08190bc030f1dcc696310 completed April 2, 2026, 2:10 a.m.
NED1 Entity disambiguation (via context triple) batch_69d29a96fc888190aec7cd364a0d7fb1 completed April 5, 2026, 5:23 p.m.
Created at: March 30, 2026, 8:58 p.m.