Triple
T4470754
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Codex 150, Bibliothèque municipale de Valenciennes |
E98489
|
entity |
| Predicate | languageOfNotableText |
P17914
|
FINISHED |
| Object | Old High German |
—
|
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: Old High German | Statement: [Codex 150, Bibliothèque municipale de Valenciennes, languageOfNotableText, Old High German]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfNotableText Context triple: [Codex 150, Bibliothèque municipale de Valenciennes, languageOfNotableText, Old High German]
-
A.
languageOfWritings
chosen
Indicates that a specified language is the one in which certain writings or written works are composed.
-
B.
languageOfBooks
Indicates the language in which the referenced books are written or published.
-
C.
typicalLanguageOfReadings
Indicates the language that is most commonly used for readings or interpretations associated with a given entity.
-
D.
isLanguageOf
Indicates that a particular language is used as the official or primary language associated with a given entity (such as a person, document, or region).
-
E.
typicalLanguages
Indicates the languages that are commonly or characteristically used, spoken, or associated with a given entity.
- 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_69b3454b4ae481908967426dd37284d6 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b356fb69a0819099f0005779f4fcac |
completed | March 13, 2026, 12:14 a.m. |
| PD | Predicate disambiguation | batch_69b3563bf4f8819081726cde3a34460b |
completed | March 13, 2026, 12:11 a.m. |
Created at: March 12, 2026, 11:34 p.m.