Triple
T2457021
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lourdes apparitions of 1858 |
E54445
|
entity |
| Predicate | numberOfApparitions |
P17874
|
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 apparitions of 1858, numberOfApparitions, 18]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfApparitions Context triple: [Lourdes apparitions of 1858, numberOfApparitions, 18]
-
A.
numberOfInstances
chosen
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
B.
appearsFor
Indicates that one entity is presented, shown, or made visible on behalf of, or in representation of, another entity.
-
C.
numberOfNames
Indicates the count of distinct names associated with a given entity.
-
D.
numberOfActs
Indicates the total count of discrete acts or actions associated with a given entity or event.
-
E.
numberOfCommonUseCharacters
Indicates the count of characters that are shared in common between two entities’ representations or strings.
- 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.