Triple
T5335945
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EATCS Award |
E123825
|
entity |
| Predicate | notableRecipient |
P108
|
FINISHED |
| Object | Dexter Kozen |
E239160
|
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: Dexter Kozen | Statement: [EATCS Award, notableRecipient, Dexter Kozen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dexter Kozen Context triple: [EATCS Award, notableRecipient, Dexter Kozen]
-
A.
Dexter Kozen
chosen
Dexter Kozen is an American theoretical computer scientist known for his influential work in logic in computer science, automata theory, and the semantics of programming languages.
-
B.
Andrew G. Myers
Andrew G. Myers is an American organic chemist renowned for his contributions to complex molecule synthesis and medicinal chemistry.
-
C.
Robert Scheifler
Robert Scheifler is a computer scientist best known for leading the development of the X Window System at MIT.
-
D.
Michael Lehmann
Michael Lehmann is an American film and television director best known for the dark comedy "Heathers" and various other Hollywood comedies.
-
E.
Gerard J. Holzmann
Gerard J. Holzmann is a computer scientist best known for creating the SPIN model checker and for his influential work in formal verification and software reliability.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85af799081909ee60bfbb65149ee |
completed | March 20, 2026, 5:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf21c20364819093387aa0e60b4291 |
completed | March 21, 2026, 10:54 p.m. |
Created at: March 20, 2026, 2 p.m.