Triple
T17254976
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lourdes |
E418856
|
entity |
| Predicate | apparitionsNumber |
P121573
|
FINISHED |
| Object | 18 |
—
|
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: 18 | Statement: [Lourdes, apparitionsNumber, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: apparitionsNumber Context triple: [Lourdes, apparitionsNumber, 18]
-
A.
apparitionWitnessCount
chosen
Indicates the number of distinct observers who witnessed a particular apparition event.
-
B.
apparitionsRecognizedBy
Indicates that certain apparitions are acknowledged, identified, or accepted as genuine by a particular person, group, or authority.
-
C.
apparitionsDate
Indicates the date on which the apparitions are reported or believed to have occurred.
-
D.
associatedWithApparition
Indicates a relationship where something is linked or connected to an apparition, such as being caused by, accompanying, or characterizing that apparition.
-
E.
apparitionsYear
Indicates the year in which the apparitions or appearances associated with an entity took place.
- 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_69d886d9ab108190b70edd8d17aa1204 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e42e6c362c819088965c6e05f33faf |
completed | April 19, 2026, 1:22 a.m. |
| PD | Predicate disambiguation | batch_69e3832a284481908a8a3da7ac91de5a |
completed | April 18, 2026, 1:12 p.m. |
Created at: April 10, 2026, 5:39 a.m.