Triple
T17872040
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henkin construction |
E446858
|
entity |
| Predicate | yields |
P490
|
FINISHED |
| Object | Henkin model |
—
|
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: Henkin model | Statement: [Henkin construction, yields, Henkin model]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Henkin model Context triple: [Henkin construction, yields, Henkin model]
-
A.
Henkin construction
chosen
Henkin construction is a model-building technique in first-order logic that extends a theory with new constants to ensure every consistent set of sentences has a model, thereby proving completeness.
-
B.
organon model of language
The organon model of language is a linguistic theory that explains language as a multifunctional tool for expressing thoughts, conveying information, and influencing others within a communicative context.
-
C.
Henkin
Henkin is a surname most notably associated with Leon Henkin, an influential logician known for his work in the foundations of mathematics and completeness in first-order logic.
-
D.
Tucker model
The Tucker model is a form of higher-order principal component analysis that decomposes a tensor into a core tensor multiplied by factor matrices along each mode, widely used for multi-way data analysis.
-
E.
Fitting semantics for modal logic
Fitting semantics for modal logic is a framework in mathematical logic that extends Kripke-style semantics to provide a more general and often intuitionistic treatment of modal operators.
- 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_69d8b9f4c22c819093c2680434472894 |
completed | April 10, 2026, 8:51 a.m. |
| NER | Named-entity recognition | batch_69e49aa30ff8819090c51c1d7767e952 |
completed | April 19, 2026, 9:04 a.m. |
Created at: April 10, 2026, 10:18 a.m.