Triple
T32706991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rabin automaton |
E836299
|
entity |
| Predicate | canRecognizeAllLanguagesOf |
P174811
|
FINISHED |
| Object | nondeterministic Büchi automaton |
—
|
LITERAL 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: nondeterministic Büchi automaton | Statement: [Rabin automaton, canRecognizeAllLanguagesOf, nondeterministic Büchi automaton]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: canRecognizeAllLanguagesOf Context triple: [Rabin automaton, canRecognizeAllLanguagesOf, nondeterministic Büchi automaton]
-
A.
recognizesLanguages
Indicates that an entity has the ability to identify, understand, or acknowledge one or more languages.
-
B.
recognizedLanguage
Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
-
C.
hasLanguages
Indicates that an entity is associated with one or more languages it uses, supports, or is expressed in.
-
D.
languageOfWorkRecognized
Indicates that a work is officially recognized as being created or expressed in a particular language.
-
E.
usesWorkingLanguagesOf
Indicates that one entity employs or operates using the working languages associated with another entity.
- F. None of above. chosen
Provenance (4 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_69f3493446148190819541f3ffe79975 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6c851d2488190a93924bca6b167d1 |
completed | May 3, 2026, 4 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f617c08190a70ba880210f908c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c77500a08190b2bdeca33bd2ac08 |
completed | May 3, 2026, 3:56 a.m. |
Created at: May 1, 2026, 1:10 a.m.