Triple
T10475936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Camino de Santiago |
E247043
|
entity |
| Predicate | hasHolyYearFrequency |
P88934
|
FINISHED |
| Object | every time 25 July falls on a Sunday |
—
|
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: every time 25 July falls on a Sunday | Statement: [Camino de Santiago, hasHolyYearFrequency, every time 25 July falls on a Sunday]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHolyYearFrequency Context triple: [Camino de Santiago, hasHolyYearFrequency, every time 25 July falls on a Sunday]
-
A.
holyYearCondition
Indicates a condition or requirement that applies specifically during a designated holy or sacred year.
-
B.
hasLiturgicalPeriod
Indicates that something is associated with, occurs during, or is assigned to a specific liturgical period within a religious calendar.
-
C.
hasLiturgicalCycle
Indicates that one entity follows, observes, or is structured according to a particular liturgical cycle associated with another entity.
-
D.
hasSpecialYear
chosen
Indicates that an entity is associated with a particular year that is distinguished or treated as exceptional in some defined context.
-
E.
hasLeapYearFrequency
Indicates how often leap years occur within a given temporal pattern or calendar system.
- 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_69d381c16c248190a2fe5b471e584e9c |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d5094f6b408190a5a26b1a82e4a02b |
completed | April 7, 2026, 1:40 p.m. |
| PD | Predicate disambiguation | batch_69d4fb84bafc8190819757b93620508a |
completed | April 7, 2026, 12:41 p.m. |
Created at: April 6, 2026, 12:21 p.m.