Triple
T6099927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruritania |
E135967
|
entity |
| Predicate | hasLanguageInferred |
P238
|
FINISHED |
| Object | German-like language |
—
|
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: German-like language | Statement: [Ruritania, hasLanguageInferred, German-like language]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageInferred Context triple: [Ruritania, hasLanguageInferred, German-like language]
-
A.
hasLanguageOn
Indicates that an entity uses or is associated with a particular language in a specific context, medium, or location.
-
B.
recognizedLanguage
chosen
Indicates that an entity has identified, detected, or acknowledged a particular language as being used or present.
-
C.
hasLanguageType
Indicates that an entity is associated with a particular type or category of language (e.g., spoken, written, programming, sign).
-
D.
hasSignificantLanguage
Indicates that an entity possesses a language that plays an important or primary role in its communication, identity, or functioning.
-
E.
hasLanguageRepresentation
Indicates that an entity is expressed, encoded, or represented using a particular natural or formal 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_69c0087cd3c48190b459848c72d84eb1 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c05b3970808190ba90f5e4235db9f2 |
completed | March 22, 2026, 9:12 p.m. |
| PD | Predicate disambiguation | batch_69c049f5ac988190b62ba565153aaa35 |
completed | March 22, 2026, 7:58 p.m. |
Created at: March 22, 2026, 4:13 p.m.