Triple
T34381821
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of Knock |
E882458
|
entity |
| Predicate | hasFirstCommissionYear |
P200010
|
FINISHED |
| Object | 1879 |
—
|
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: 1879 | Statement: [Our Lady of Knock, hasFirstCommissionYear, 1879]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFirstCommissionYear Context triple: [Our Lady of Knock, hasFirstCommissionYear, 1879]
-
A.
hasFirstCohortYear
Indicates the year in which the first cohort associated with an entity began or was established.
-
B.
hasInceptionPeriod
Indicates the time span or period during which something begins or comes into existence.
-
C.
hasFirstExplorationYear
Indicates the year in which an entity was first explored or investigated.
-
D.
hasFirstProofYear
Indicates the year in which something was first proven or formally demonstrated to be true.
-
E.
hasApproximateCommissioningPeriod
Indicates that an entity is associated with a commissioning time frame that is known only approximately rather than as a precise date.
- 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_69ff6a4ce9a08190b98abde3a170dd69 |
completed | May 9, 2026, 5:09 p.m. |
| PD | Predicate disambiguation | batch_69ff69c11634819089d1084bd2c11534 |
completed | May 9, 2026, 5:07 p.m. |
| PDg | Predicate description generation | batch_69ff6a4c32dc819097f591944bee8851 |
completed | May 9, 2026, 5:09 p.m. |
Created at: May 1, 2026, 1:59 a.m.