Triple
T5407121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wolfgang Grajonca |
E120918
|
entity |
| Predicate | childhoodExperience |
P2854
|
FINISHED |
| Object | escaped Nazi Germany as a child refugee |
—
|
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: escaped Nazi Germany as a child refugee | Statement: [Wolfgang Grajonca, childhoodExperience, escaped Nazi Germany as a child refugee]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: childhoodExperience Context triple: [Wolfgang Grajonca, childhoodExperience, escaped Nazi Germany as a child refugee]
-
A.
spentChildhoodIn
Indicates that a person or entity spent the majority or formative years of their childhood in a particular place or location.
-
B.
experiences
chosen
Indicates that an entity undergoes, feels, or is affected by a particular event, state, or condition.
-
C.
gaveFirsthandExperienceOf
Indicates that one entity directly provided another entity with personal, firsthand experience of something, rather than secondhand or indirect knowledge.
-
D.
children
Indicates that one entity is the offspring or direct descendant of another entity.
-
E.
childhoodFriend
Indicates that two people were close friends during their childhood period.
- 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_69bd46391c0c81909fa484446732b6a3 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd8793ab3c81909992b257d462a554 |
completed | March 20, 2026, 5:44 p.m. |
| PD | Predicate disambiguation | batch_69bd8467e6b48190b9eaa9de67072e06 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:05 p.m.