Triple
T15137764
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Prince Frederick Henry of Orange |
E361598
|
entity |
| Predicate | depictsPersonReligion |
P83945
|
FINISHED |
| Object | Protestantism |
—
|
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: Protestantism | Statement: [Portrait of Prince Frederick Henry of Orange, depictsPersonReligion, Protestantism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: depictsPersonReligion Context triple: [Portrait of Prince Frederick Henry of Orange, depictsPersonReligion, Protestantism]
-
A.
depictsPerson
Indicates that one entity visually represents or portrays a specific person.
-
B.
religionOfCharacterPortrayed
chosen
Indicates that a work portrays a character as adhering to or being associated with a particular religion.
-
C.
portraysReligionAs
Indicates that one entity represents, depicts, or characterizes a religion in a particular way.
-
D.
depictedDeity
Indicates that one entity is a deity who is shown or represented in an image, artwork, or visual depiction associated with another entity.
-
E.
hasReligiousCharacter
Indicates that an entity possesses a religious nature, function, or affiliation, or is characterized by religious aspects or significance.
- 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_69d85a06450081909c5a14ea9851a15e |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e005b59b488190b0016970647e7483 |
completed | April 15, 2026, 9:40 p.m. |
| PD | Predicate disambiguation | batch_69deb9713fe881909dec2fd3f6c84b39 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:07 a.m.