Triple
T19070053
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ovid's Fasti |
E466767
|
entity |
| Predicate | coversMonths |
P6433
|
FINISHED |
| Object | January |
—
|
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: January | Statement: [Ovid's Fasti, coversMonths, January]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coversMonths Context triple: [Ovid's Fasti, coversMonths, January]
-
A.
appliesDuringMonths
Indicates that something is valid, active, or in effect only during specific months of the year.
-
B.
hasMonth
chosen
Indicates that something is associated with, occurs in, or is assigned to a specific month.
-
C.
hasMonthCount
Indicates a relationship where an entity is associated with a specific number of months.
-
D.
coversPeriodStart
Indicates that the time span or coverage of one entity begins at, or includes, the specified starting point in time of another entity or period.
-
E.
coversYearsTo
Indicates a temporal relationship where one entity spans, includes, or extends up to a specified year or range of years represented by the other 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e19caa708190876a2cb06aa0c9cc |
completed | April 20, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69e4b99f602881909eeb9c780597e0e6 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:03 p.m.