Triple
T25890358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alonso de Molina |
E652312
|
entity |
| Predicate | primaryAudienceOfWorks |
P10804
|
FINISHED |
| Object | Spanish missionaries in New Spain |
—
|
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: Spanish missionaries in New Spain | Statement: [Alonso de Molina, primaryAudienceOfWorks, Spanish missionaries in New Spain]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primaryAudienceOfWorks Context triple: [Alonso de Molina, primaryAudienceOfWorks, Spanish missionaries in New Spain]
-
A.
targetAudienceOfOriginWork
Indicates the intended audience or demographic group for which the original work was created.
-
B.
primaryDepictionWork
Indicates that a work is the main or most significant subject depicted in a given representation or resource.
-
C.
typicalAudience
chosen
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
-
D.
targetAudienceWithinFiction
Indicates that the intended audience of a work exists as characters or entities within the fictional world depicted by that work.
-
E.
book3Audience
Indicates that a particular book is intended for or targeted toward a specific audience.
- 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_69e7ab3b92cc81908febd90317862647 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69fd0d0ba5c48190bddb3f0e6637544c |
completed | May 7, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69fd0c4324a8819086c90adf46216e0e |
completed | May 7, 2026, 10:03 p.m. |
Created at: April 22, 2026, 8:19 a.m.