Triple
T10410098
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Legenda Aurea |
E245364
|
entity |
| Predicate | wasWidelyCirculated |
P69873
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Legenda Aurea, wasWidelyCirculated, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wasWidelyCirculated Context triple: [Legenda Aurea, wasWidelyCirculated, true]
-
A.
popularizedIn
Indicates that something became widely known, accepted, or fashionable within a particular place, time period, or context.
-
B.
circulatedAs
Indicates that something was distributed, shared, or passed around in the form or role specified by the related entity.
-
C.
hadCirculationIn
Indicates that an entity (such as a publication or medium) had its copies distributed or circulated within a specified location or region.
-
D.
widelyCoveredBy
Indicates that something (such as an event, topic, or issue) receives extensive attention or reporting from many media outlets or information sources.
-
E.
isWidelyKnown
chosen
Indicates that something is generally recognized or familiar to a large number of people.
- 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_69d381be340c8190b05998703d42d224 |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4e9fb98748190a3a6c161edd8f400 |
completed | April 7, 2026, 11:26 a.m. |
| PD | Predicate disambiguation | batch_69d4dfb6f160819090040644a12395ec |
completed | April 7, 2026, 10:43 a.m. |
Created at: April 6, 2026, 12:09 p.m.