Triple
T15137753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Portrait of Prince Frederick Henry of Orange |
E361598
|
entity |
| Predicate | hasPortrayedPersonDateOfDeath |
P16526
|
FINISHED |
| Object | 1647 |
—
|
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: 1647 | Statement: [Portrait of Prince Frederick Henry of Orange, hasPortrayedPersonDateOfDeath, 1647]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPortrayedPersonDateOfDeath Context triple: [Portrait of Prince Frederick Henry of Orange, hasPortrayedPersonDateOfDeath, 1647]
-
A.
yearOfDeath
chosen
Indicates the specific year in which an entity (typically a person or organism) died.
-
B.
honorsPersonDiedIn
Indicates that something serves as a tribute or commemoration to the person who died in a particular event, place, or circumstance.
-
C.
diedInSameYearAs
Indicates that two entities each died in the same calendar year.
-
D.
dateOfDeath
Indicates the specific date on which an individual or entity died.
-
E.
deathYearInferredFrom
Indicates that an entity’s year of death is not directly known but has been deduced based on other available information or evidence.
- 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.