Triple
T35568169
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zeitz labor camp |
E1027835
|
entity |
| Predicate | hasFictionalPrisoner |
P48975
|
FINISHED |
| Object | protagonist of Fatelessness |
—
|
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: protagonist of Fatelessness | Statement: [Zeitz labor camp, hasFictionalPrisoner, protagonist of Fatelessness]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalPrisoner Context triple: [Zeitz labor camp, hasFictionalPrisoner, protagonist of Fatelessness]
-
A.
fictionalPrisoner
chosen
Indicates that an entity is portrayed as a prisoner within a fictional or narrative context.
-
B.
hasPrison
Indicates that one entity possesses, contains, or is the location of a prison associated with another entity.
-
C.
hasBeenImprisonedBy
Indicates that one entity has been confined or incarcerated under the authority or control of another entity.
-
D.
hasBeenImprisoned
Indicates that an entity has been confined or incarcerated in a prison or similar detention facility at some point in time.
-
E.
fictionalPrisonName
Indicates that an entity is identified by the name of a fictional prison.
- 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_69f76e020fd8819081cb080e7e203083 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69ffdf47d9608190830ca23d9cef6409 |
completed | May 10, 2026, 1:28 a.m. |
| PD | Predicate disambiguation | batch_69ffdf00e2b4819082dd5cb78f316baf |
completed | May 10, 2026, 1:27 a.m. |
Created at: May 3, 2026, 4:04 p.m.