Triple
T10991867
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Koebe quarter theorem |
E259770
|
entity |
| Predicate | typicalNormalization |
P12230
|
FINISHED |
| Object | f(0)=0 |
—
|
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: f(0)=0 | Statement: [Koebe quarter theorem, typicalNormalization, f(0)=0]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNormalization Context triple: [Koebe quarter theorem, typicalNormalization, f(0)=0]
-
A.
normalizationAttempt
Indicates an effort to convert something into a standard or consistent form according to defined rules or criteria.
-
B.
refinesNormalization
Indicates that one normalization process or scheme improves, clarifies, or makes more precise another existing normalization.
-
C.
usesNormalization
Indicates that one entity applies or relies on a normalization process or technique in relation to another entity or data.
-
D.
typicalIn
chosen
Indicates that something commonly occurs, appears, or is found within a given context, category, or environment.
-
E.
normType
Indicates the specific category or classification of a norm that governs or constrains an entity or situation.
- F. None of above.
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_69d6aa8a6a548190a750f944ccdc8064 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d795d1e918819090c71f5a077fa15a |
completed | April 9, 2026, 12:04 p.m. |
| PD | Predicate disambiguation | batch_69d72e93ac648190b46c5d12bf3eb1e9 |
completed | April 9, 2026, 4:44 a.m. |
Created at: April 8, 2026, 9:24 p.m.