Triple
T8954750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mariazell Basilica |
E213444
|
entity |
| Predicate | earliestDocumentedMention |
P3921
|
FINISHED |
| Object | 1243 |
—
|
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: 1243 | Statement: [Mariazell Basilica, earliestDocumentedMention, 1243]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: earliestDocumentedMention Context triple: [Mariazell Basilica, earliestDocumentedMention, 1243]
-
A.
earliestWellKnownExample
Indicates that one entity is the earliest well-known example or instance of the other entity.
-
B.
firstClearlyAttestedIn
chosen
Indicates the earliest known point in time or source where something is clearly documented or evidenced.
-
C.
earliestAttestedStatus
Indicates the earliest known or recorded status that has been documented for an entity.
-
D.
earliestKnownHolder
Indicates that the subject is the first known entity in time to have possessed, held, or been assigned the object.
-
E.
eraMentioned
Indicates that a specific historical or temporal era is explicitly referenced or mentioned in a given context.
- 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_69ca8399ad2081909f8fa41d4314c215 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc6724f3e4819092c6b13d80871e80 |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 7 p.m.