Triple
T4261776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gesta Francorum |
E96119
|
entity |
| Predicate | modernEditions |
P6687
|
FINISHED |
| Object | edited and translated in various modern languages |
—
|
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: edited and translated in various modern languages | Statement: [Gesta Francorum, modernEditions, edited and translated in various modern languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: modernEditions Context triple: [Gesta Francorum, modernEditions, edited and translated in various modern languages]
-
A.
hasModernEditions
chosen
Indicates that an original work or text has one or more updated or contemporary published editions.
-
B.
numberOfEditions
Indicates the total count of distinct editions associated with a given entity.
-
C.
notableEdition
Indicates that a particular edition or version of a work is especially significant or noteworthy in relation to that work.
-
D.
hasYoungReadersEdition
Indicates that a work has a specially adapted edition intended for young or juvenile readers.
-
E.
laterEditionParatext
Indicates that the paratext is taken from or associated with a later edition of the work than the primary text or base edition under consideration.
- 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_69b3454095ac81909c2494f7ff294af1 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b34f82b2688190bf4c581e13a9c4b9 |
completed | March 12, 2026, 11:42 p.m. |
| PD | Predicate disambiguation | batch_69b347f8dcb08190a725c1f7fb5a7466 |
completed | March 12, 2026, 11:10 p.m. |
Created at: March 12, 2026, 11:06 p.m.