Triple
T33351853
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Our Lady of Luján |
E853963
|
entity |
| Predicate | legendaryOriginYear |
P85854
|
FINISHED |
| Object | 1630 |
—
|
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: 1630 | Statement: [Our Lady of Luján, legendaryOriginYear, 1630]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: legendaryOriginYear Context triple: [Our Lady of Luján, legendaryOriginYear, 1630]
-
A.
legendaryPeriod
Indicates a time span associated with legends or mythic events rather than strictly historical chronology.
-
B.
foundingLegendDate
chosen
Indicates the date associated with the legendary or mythic founding of an entity, rather than its historically verified establishment date.
-
C.
originYear
Indicates the year in which something first originated, was created, or began.
-
D.
dateInLegendarium
Indicates that a given date occurs within the fictional historical timeline (legendarium) of a particular narrative world.
-
E.
hasHistoricalOriginInYear
Indicates that something first originated, began, or came into existence in a specified calendar year.
- 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_69f3496acbc8819099fd0305ecc42080 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6f8164698819090c1b471f1caa4c6 |
completed | May 3, 2026, 7:24 a.m. |
| PD | Predicate disambiguation | batch_69f6f6619404819084662aef1238261c |
completed | May 3, 2026, 7:16 a.m. |
Created at: May 1, 2026, 1:34 a.m.