Triple
T28605501
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roland Deschain's ka-tet |
E724034
|
entity |
| Predicate | languageOfOriginTerm |
P121450
|
FINISHED |
| Object | High Speech |
—
|
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: High Speech | Statement: [Roland Deschain's ka-tet, languageOfOriginTerm, High Speech]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfOriginTerm Context triple: [Roland Deschain's ka-tet, languageOfOriginTerm, High Speech]
-
A.
languageOfCoinedTerm
chosen
Indicates the language in which a particular term was originally coined or first formulated.
-
B.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
C.
languageTerm
Indicates that one entity is a linguistic expression (word, phrase, or term) used to denote or label the other entity.
-
D.
hasNameEtymologyIn
Indicates that the origin or derivation of an entity’s name is based in, or traceable to, a specified source such as a language, place, or cultural context.
-
E.
vernacularOf
Indicates that one language or dialect is the everyday, locally used form corresponding to another, more general or standard language.
- 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_69f01d816d7c8190a1fe27e3434041dc |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69fdee770af48190aca2670db50f8b49 |
completed | May 8, 2026, 2:08 p.m. |
| PD | Predicate disambiguation | batch_69fdecec98a08190a357d816dc2a6dbe |
completed | May 8, 2026, 2:02 p.m. |
Created at: April 28, 2026, 4:27 a.m.