Triple
T15137752
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Prince Frederick Henry of Orange |
E361598
|
entity |
| Predicate | hasPortrayedPersonDateOfBirth |
P105043
|
FINISHED |
| Object | 1584 |
—
|
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: 1584 | Statement: [Portrait of Prince Frederick Henry of Orange, hasPortrayedPersonDateOfBirth, 1584]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortrayedPersonDateOfBirth Context triple: [Portrait of Prince Frederick Henry of Orange, hasPortrayedPersonDateOfBirth, 1584]
-
A.
creatorBirthDate
Indicates the date on which the creator of an entity was born.
-
B.
depictsPersonDateOfBirth
chosen
Indicates that the subject is a depiction (e.g., an image or representation) that shows or is associated with the date of birth of a specific person.
-
C.
portraysCharacterBirthName
Indicates that one entity depicts or represents the birth name of a character associated with another entity.
-
D.
refersToPersonBornOn
Indicates that one entity makes reference to, or is associated with, a specific person who was born on a given date.
-
E.
authorBirthYear
Indicates the year in which the author of a work or text was born.
- 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.