Triple
T114470
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Royal Road |
E2313
|
entity |
| Predicate | labelType |
P1081
|
FINISHED |
| Object | traditional name |
—
|
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: traditional name | Statement: [The Royal Road, labelType, traditional name]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: labelType Context triple: [The Royal Road, labelType, traditional name]
-
A.
notationType
Indicates the specific system or style of notation used to represent or encode something (such as music, math, or language).
-
B.
nameType
chosen
Indicates the specific category or type of a name associated with an entity (e.g., legal name, nickname, alias, or preferred name).
-
C.
nativeLabel
Indicates the label or name of an entity expressed in its own native or original language.
-
D.
leafType
Indicates the specific kind or classification of leaf associated with an entity.
-
E.
fieldType
Indicates the classification or category that defines the nature or kind of a given field within a structure or context.
- 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_69a24fcdaeb48190a2d796677e4b3281 |
completed | Feb. 28, 2026, 2:15 a.m. |
| NER | Named-entity recognition | batch_69a25760af348190bf402089c240887d |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564417848190a8a8a38e97348963 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:20 a.m.