Triple
T38663052
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Homilies of the Church of England |
E940382
|
entity |
| Predicate | totalNumberOfHomilies |
P145364
|
FINISHED |
| Object | 33 |
—
|
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: 33 | Statement: [Homilies of the Church of England, totalNumberOfHomilies, 33]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: totalNumberOfHomilies Context triple: [Homilies of the Church of England, totalNumberOfHomilies, 33]
-
A.
approximateNumberOfHomilies
Indicates the estimated count of homilies associated with an entity, rather than an exact number.
-
B.
numberOfHomiliesInSeries
chosen
Indicates the total count of homilies that belong to a given homily series.
-
C.
numberOfSermons
Indicates the quantity or count of sermons associated with a given entity or context.
-
D.
eucharisticAnaphorasCount
Indicates the number of eucharistic anaphoras (central Eucharistic prayers) associated with or used in a given liturgical context.
-
E.
numberOfSpeeches
Indicates the total count of speeches associated with a given entity or event.
- 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_69f76edfde348190bf6529d9f49ecd62 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fd389cb28c819099a77e28d25f258a |
completed | May 8, 2026, 1:13 a.m. |
| PD | Predicate disambiguation | batch_69fd3826d8048190ada79a5868d1d7f3 |
completed | May 8, 2026, 1:11 a.m. |
Created at: May 3, 2026, 4:33 p.m.