Triple
T18793316
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Arend Heyting |
E459570
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Heyting |
—
|
NE NERFINISHED |
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: Heyting | Statement: [Arend Heyting, familyName, Heyting]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heyting Context triple: [Arend Heyting, familyName, Heyting]
-
A.
Gentzen
Gentzen is a surname most notably associated with Gerhard Gentzen, a pioneering German logician known for his foundational work in proof theory and natural deduction.
-
B.
Arend Heyting
chosen
Arend Heyting was a Dutch mathematician and logician best known as a principal founder and formalizer of intuitionistic logic and mathematics.
-
C.
Hájek
Hájek is a Czech surname borne by numerous notable figures in fields such as politics, science, and the arts.
-
D.
Hilberseimer
Hilberseimer is the surname of Ludwig Hilberseimer, a German-American architect and urban planner known for his influential modernist city planning theories.
-
E.
Huizenga
Huizenga is a Dutch-origin surname most notably associated with American businessman Wayne Huizenga, who built major companies such as Waste Management, Blockbuster, and AutoNation.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d396f54c8190ba49db31e8743842 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e59787e5988190883ed575ab4b6dec |
completed | April 20, 2026, 3:03 a.m. |
Created at: April 10, 2026, 11:53 a.m.