Triple
T29411224
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Farfa Abbey |
E745897
|
entity |
| Predicate | hasLanguageOfHistoricalDocuments |
P30358
|
FINISHED |
| Object | Latin |
—
|
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: Latin | Statement: [Farfa Abbey, hasLanguageOfHistoricalDocuments, Latin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLanguageOfHistoricalDocuments Context triple: [Farfa Abbey, hasLanguageOfHistoricalDocuments, Latin]
-
A.
languageOfHistoricalRecord
chosen
Indicates the language in which a given historical record is written or recorded.
-
B.
historicalLanguage
Indicates that one language is a historical or earlier form/ancestor of another language.
-
C.
historicalLanguageOfScholarship
Indicates that a language has historically been used as a primary medium of scholarly, academic, or learned communication for a given community, region, or tradition.
-
D.
historicalLanguageOfBearers
Indicates that the specified language is historically spoken or used by the bearers of a given name, title, or designation.
-
E.
historicalLanguageStatus
Indicates that a language had a particular official, social, or functional status during a past historical period.
- 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_69f0a79eb7d081908c67197a5f347e68 |
completed | April 28, 2026, 12:27 p.m. |
| NER | Named-entity recognition | batch_69fd509e6bc08190b263923c2f40fea3 |
completed | May 8, 2026, 2:55 a.m. |
| PD | Predicate disambiguation | batch_69fd4fd1a58881909d4b84de1b24e380 |
completed | May 8, 2026, 2:52 a.m. |
Created at: April 28, 2026, 2:57 p.m.