Triple
T5367630
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Japanese Lover |
E103167
|
entity |
| Predicate | featuresCharacterBackground |
P39316
|
FINISHED |
| Object | Holocaust survivor family |
—
|
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: Holocaust survivor family | Statement: [The Japanese Lover, featuresCharacterBackground, Holocaust survivor family]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: featuresCharacterBackground Context triple: [The Japanese Lover, featuresCharacterBackground, Holocaust survivor family]
-
A.
protagonistBackground
Indicates that one entity serves as the background, history, or prior circumstances of the protagonist entity in a narrative or story.
-
B.
hasProtagonistBackground
chosen
Indicates that a work or narrative features a specified background or origin story for its main protagonist.
-
C.
characterOrigin
Indicates the source, background, or initial context from which a character originates.
-
D.
featuresCharacterRole
Indicates that a work includes a character appearing in a specific narrative or functional role.
-
E.
featuresProtagonistOccupation
Indicates that the work’s main character has a specified occupation or job role.
- 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd8684103081908ed79625b59e4b24 |
completed | March 20, 2026, 5:40 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.