Triple

T15448296
Position Surface form Disambiguated ID Type / Status
Subject Gretl von Trapp E370080 entity
Predicate nickname P55 FINISHED
Object Gretl E1145582 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: Gretl | Statement: [Gretl von Trapp, nickname, Gretl]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Gretl
Context triple: [Gretl von Trapp, nickname, Gretl]
  • A. Gretl chosen
    Gretl is the nickname of Gretl Braun, the younger sister of Eva Braun who was closely associated with Adolf Hitler’s inner circle in Nazi Germany.
  • B. Stata
    Stata is a commercial statistical software package widely used in research for data management, advanced statistical analysis, and graphical visualization.
  • C. Stata
    Stata is a prominent Massachusetts Institute of Technology building known for its striking deconstructivist design by architect Frank Gehry and its role as a hub for computer science and artificial intelligence research.
  • D. ESS (Emacs Speaks Statistics)
    ESS (Emacs Speaks Statistics) is an Emacs-based add-on package that provides an integrated, script-oriented environment for interactive statistical programming and data analysis, especially with R and other statistical languages.
  • E. GSL
    GSL is the vehicle registration code assigned to cars registered in a specific district of Poland’s Pomeranian Voivodeship.
  • 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_69d85a19180081909925012fbf4e62a3 completed April 10, 2026, 2:02 a.m.
NER Named-entity recognition batch_69e03ef9334c81908541e231b43eb012 completed April 16, 2026, 1:44 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff21afb6f4819094162ca842b7eb60 completed May 9, 2026, 11:59 a.m.
Created at: April 10, 2026, 3:21 a.m.