Triple
T34896976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Easter Week VII in the Roman Rite |
E1006461
|
entity |
| Predicate | hasSeasonalPreface |
P201414
|
FINISHED |
| Object | Easter prefaces |
—
|
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: Easter prefaces | Statement: [Easter Week VII in the Roman Rite, hasSeasonalPreface, Easter prefaces]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeasonalPreface Context triple: [Easter Week VII in the Roman Rite, hasSeasonalPreface, Easter prefaces]
-
A.
hasSeasonalNature
Indicates that something exhibits characteristics, behavior, or occurrence patterns that vary according to specific seasons or times of the year.
-
B.
hasSeason
Indicates that an entity possesses, occurs during, or is associated with a particular season or set of seasons.
-
C.
hasSeasonalCounterpart
Indicates that one entity corresponds to another entity that appears or is relevant in a different season as its counterpart.
-
D.
hasSeasonalText
Indicates that an entity is associated with text that is specific to or varies by a particular season or time of year.
-
E.
hasSeasonalStatus
Indicates that an entity’s status, availability, or condition varies according to a particular season or time of year.
- F. None of above. chosen
Provenance (4 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_69f76dbfe5788190ad8b64f241f470c8 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fff328ddc0819080642334a41fcf95 |
completed | May 10, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69fff2e0971c819081aa66f4a6a34b28 |
completed | May 10, 2026, 2:52 a.m. |
| PDg | Predicate description generation | batch_69fff327d7788190a41ea5cbae060177 |
completed | May 10, 2026, 2:53 a.m. |
Created at: May 3, 2026, 4 p.m.