Triple
T2384361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zohar Manna |
E46383
|
entity |
| Predicate | notableStudent |
P4838
|
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: [Zohar Manna, notableStudent, Dexter Kozen]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dexter Kozen Context triple: [Zohar Manna, notableStudent, 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.
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.
-
D.
John Knill
John Knill is a distinguished geologist recognized for his significant contributions to the field, as evidenced by honors such as the William Smith Medal.
-
E.
Johannes Eisermann
Johannes Eisermann is a scholar known for his professorship at the European University Viadrina in Frankfurt (Oder), where he has made notable academic contributions.
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7bc87d0819090cd9d19d748bcc3 |
completed | March 7, 2026, 6:37 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aea8bae2ec8190962479832bf7762e |
completed | March 9, 2026, 11:02 a.m. |
Created at: March 4, 2026, 7:57 p.m.