Triple
T3574897
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Laura subcamp |
E75662
|
entity |
| Predicate | hasSurvivorTestimonies |
P7873
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Laura subcamp, hasSurvivorTestimonies, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurvivorTestimonies Context triple: [Laura subcamp, hasSurvivorTestimonies, yes]
-
A.
hasTestimony
chosen
Indicates that an entity provides, contains, or is associated with a formal statement or account (testimony) about another entity or event.
-
B.
savedByTestimonyOf
Indicates that an entity is rescued, delivered, or brought to salvation as a result of another entity’s testimony or witness.
-
C.
hasSurvivors
Indicates that one or more entities continue to exist or remain alive after a particular event, condition, or incident.
-
D.
survivingPerpetrators
Indicates that the referenced individuals are perpetrators of an act or event who are still alive following that act or event.
-
E.
gaveTestimonyIn
Indicates that one entity provided formal testimony or a statement in an official proceeding, event, or context associated with another entity.
- 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_69ad85d5e3008190bdfe0bacdd1f5a1b |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc0d928f08190830347b3b032178a |
completed | March 8, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69adb8364d848190a96a9bc7a6126af2 |
completed | March 8, 2026, 5:56 p.m. |
Created at: March 8, 2026, 3:21 p.m.