Triple
T3527776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Karl Harrer |
E74581
|
entity |
| Predicate | citizenshipStatusDuringActivity |
P31432
|
FINISHED |
| Object | citizen of Germany |
—
|
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: citizen of Germany | Statement: [Karl Harrer, citizenshipStatusDuringActivity, citizen of Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: citizenshipStatusDuringActivity Context triple: [Karl Harrer, citizenshipStatusDuringActivity, citizen of Germany]
-
A.
immigrationStatusBeforeCitizenship
Indicates the legal immigration status an individual held prior to obtaining citizenship.
-
B.
citizenshipDuringLifetime
chosen
Indicates that an entity held citizenship in a particular country or political unit at some point during its lifetime.
-
C.
dualCitizenshipStatus
Indicates that an entity holds legal citizenship in two different countries simultaneously.
-
D.
requiresCitizenship
Indicates that one entity can only obtain, access, or participate in another entity if it holds citizenship of a specified country or jurisdiction.
-
E.
residencyStatus
Indicates the legal or official residential classification of an entity within a particular jurisdiction or context.
- 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_69ad85d0c5488190a3d8e02ebd01a1aa |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbc6d099c8190b2b1e65a56e52089 |
completed | March 8, 2026, 6:14 p.m. |
| PD | Predicate disambiguation | batch_69adae121a048190b03825a001d21f49 |
completed | March 8, 2026, 5:12 p.m. |
Created at: March 8, 2026, 3:19 p.m.