Triple

T4303193
Position Surface form Disambiguated ID Type / Status
Subject Monowitz-Buna E99888 entity
Predicate alsoKnownAs P39 FINISHED
Object Buna-Monowitz E99888 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: Buna-Monowitz | Statement: [Monowitz-Buna, alsoKnownAs, Buna-Monowitz]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Buna-Monowitz
Context triple: [Monowitz-Buna, alsoKnownAs, Buna-Monowitz]
  • A. Erwin
    Erwin is a masculine given name of German origin, historically associated with figures such as the World War II field marshal Erwin Rommel.
  • B. Monowitz-Buna chosen
    Monowitz-Buna was a Nazi German concentration and forced-labor camp near Auschwitz, primarily used to supply slave labor for the IG Farben synthetic rubber and fuel plant during World War II.
  • C. Shimon
    Shimon is a given name most notably borne by Shimon Peres, the former President and Prime Minister of Israel and Nobel Peace Prize laureate.
  • D. Gunta
    Gunta is a given name most notably borne by Gunta Stölzl, a pioneering textile artist and the only female master at the Bauhaus school.
  • E. Dorohusk
    Dorohusk is a village in eastern Poland near the Ukrainian border, known as an important road and rail border crossing point between the two countries.
  • 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_69b345528ebc8190b5abc7e95094792d completed March 12, 2026, 10:59 p.m.
NER Named-entity recognition batch_69b350b792608190ac778b79c740256a completed March 12, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5c7507f1081909cf737dff00542d9 completed March 14, 2026, 8:38 p.m.
Created at: March 12, 2026, 11:08 p.m.