Triple
T19083137
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Christian Rosenkreuz |
E467078
|
entity |
| Predicate | firstMentionedInYearApprox |
P98261
|
FINISHED |
| Object | 1614 |
—
|
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: 1614 | Statement: [Christian Rosenkreuz, firstMentionedInYearApprox, 1614]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstMentionedInYearApprox Context triple: [Christian Rosenkreuz, firstMentionedInYearApprox, 1614]
-
A.
ageFirstMentioned
chosen
Indicates the point in time or age at which an entity is first referenced or mentioned in a given context.
-
B.
firstCelebratedInYear
Indicates the year in which something (such as an event, holiday, or celebration) was first observed or celebrated.
-
C.
firstAppearedAt
Indicates the point in time or specific event at which an entity was first introduced, observed, or became known.
-
D.
firstPublishedInWorkYear
Indicates the year in which a work was first published.
-
E.
firstClearlyRecognizedIn
Indicates the point in time or context when something was first clearly identified, acknowledged, or distinguished as such.
- 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_69d8dd04f4488190b1121cc53ef2bfd6 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5e2eab58c8190a987c88d633c92ec |
completed | April 20, 2026, 8:25 a.m. |
| PD | Predicate disambiguation | batch_69e4b9a604308190a3235184f9f2c056 |
completed | April 19, 2026, 11:16 a.m. |
Created at: April 10, 2026, 12:04 p.m.