Triple
T34381822
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of Knock |
E882458
|
entity |
| Predicate | hasSecondCommissionYear |
P201056
|
FINISHED |
| Object | 1936 |
—
|
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: 1936 | Statement: [Our Lady of Knock, hasSecondCommissionYear, 1936]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSecondCommissionYear Context triple: [Our Lady of Knock, hasSecondCommissionYear, 1936]
-
A.
hasFirstCommissionYear
Indicates the year in which an entity received its first official commission or assignment.
-
B.
hasSecond
Indicates that one entity is the second item, position, or element in an ordered sequence or pair relative to another entity.
-
C.
commissionYear
Indicates the year in which something (such as a work, project, or asset) was formally commissioned or authorized to be created or undertaken.
-
D.
hasSecondTerm
Indicates that an entity is associated with a second term in a sequence, pair, or ordered relationship.
-
E.
hasFirstCohortYear
Indicates the year in which the first cohort associated with an entity began or was established.
- 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_69f349c0219881909393bbbc1edc8161 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69ffc516d1908190b475f5a6156b0ca8 |
completed | May 9, 2026, 11:36 p.m. |
| PD | Predicate disambiguation | batch_69ffc4a946e08190b3535a5dc15ac484 |
completed | May 9, 2026, 11:35 p.m. |
| PDg | Predicate description generation | batch_69ffc515e4b08190810b2a29b2885162 |
completed | May 9, 2026, 11:36 p.m. |
Created at: May 1, 2026, 1:59 a.m.