Triple
T16991932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Coxeter–Dynkin diagrams |
E412212
|
entity |
| Predicate | nodeMeaning |
P126081
|
FINISHED |
| Object | node corresponds to a simple root |
—
|
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: node corresponds to a simple root | Statement: [Coxeter–Dynkin diagrams, nodeMeaning, node corresponds to a simple root]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nodeMeaning Context triple: [Coxeter–Dynkin diagrams, nodeMeaning, node corresponds to a simple root]
-
A.
objectMeaning
Indicates that one entity represents, expresses, or conveys the meaning or semantic content of another entity.
-
B.
stringMeaning
Indicates that one entity represents the semantic content or interpretation of a given string associated with another entity.
-
C.
deviceMeaning
Indicates that one entity specifies or conveys the functional meaning, purpose, or interpretation of a device-related entity.
-
D.
textMeaning
Indicates that one text expresses, conveys, or corresponds to a particular meaning or semantic content.
-
E.
oniMeaning
Indicates that one entity expresses or conveys the meaning or sense of another entity (such as a word, phrase, or symbol).
- 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_69d886cb581c8190ab05f4b429c9cd85 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3d283d2388190a78bf8d179e83fdc |
completed | April 18, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69e35d552bc08190af17ef7659e094ef |
completed | April 18, 2026, 10:30 a.m. |
| PDg | Predicate description generation | batch_69e378e037c88190935d732e0f10d5d7 |
completed | April 18, 2026, 12:28 p.m. |
Created at: April 10, 2026, 5:32 a.m.