Triple

T8520828
Position Surface form Disambiguated ID Type / Status
Subject Wesley A. Clark E201688 entity
Predicate coDesignedWith P30900 FINISHED
Object Charles Molnar E748086 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: Charles Molnar | Statement: [Wesley A. Clark, coDesignedWith, Charles Molnar]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Charles Molnar
Context triple: [Wesley A. Clark, coDesignedWith, Charles Molnar]
  • A. Charles Molnar chosen
    Charles Molnar was an American computer engineer best known as the co-designer of the LINC, one of the earliest minicomputers and a pioneering machine in interactive computing.
  • B. Charles Bergstresser
    Charles Bergstresser was an American journalist and financier best known as one of the co-founders of The Wall Street Journal.
  • C. Ralph Koltai
    Ralph Koltai was a prominent British theatre designer renowned for his innovative, sculptural stage sets that transformed post-war European theatre aesthetics.
  • D. Laszlo Molnar
    Laszlo Molnar is a software developer and author known for creating the UPX (Ultimate Packer for Executables) executable compression tool.
  • E. George Katona
    George Katona was a Hungarian-American psychologist and economist known as a pioneer of behavioral economics and consumer sentiment research.
  • 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_69ca8321bb44819081b74df0b710276d completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cbe628f8c48190a35201f9fde605cc completed March 31, 2026, 3:20 p.m.
NED1 Entity disambiguation (via context triple) batch_69cecc53555c8190b910b3220bd701b4 completed April 2, 2026, 8:06 p.m.
Created at: March 30, 2026, 6:16 p.m.