Triple
T1981719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ogygia |
E43040
|
entity |
| Predicate | languageOfEarliestSource |
P3926
|
FINISHED |
| Object | Ancient Greek |
—
|
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: Ancient Greek | Statement: [Ogygia, languageOfEarliestSource, Ancient Greek]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfEarliestSource Context triple: [Ogygia, languageOfEarliestSource, Ancient Greek]
-
A.
languageOfEarliestForm
chosen
Indicates the language in which the earliest known form or attested version of something (e.g., a text, name, or expression) is recorded.
-
B.
languageOfSources
Indicates that the specified language is the language in which the referenced sources or source materials are expressed.
-
C.
languageOfHistoricalRecord
Indicates the language in which a given historical record is written or recorded.
-
D.
earliestTextsIn
Indicates that certain texts are among the earliest known examples found in or associated with a particular place or context.
-
E.
firstClearlyAttestedIn
Indicates the earliest known point in time or source where something is clearly documented or evidenced.
- 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_69a88713ddc88190a969715658ebe7a8 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb96f932881908bebfc4176fda7c0 |
completed | March 7, 2026, 5:36 a.m. |
| PD | Predicate disambiguation | batch_69abb798d288819083132cf14605bd02 |
completed | March 7, 2026, 5:28 a.m. |
Created at: March 4, 2026, 7:37 p.m.