Triple
T27432088
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Max von Boehn |
E690668
|
entity |
| Predicate | hasCitizenshipDuringActivity |
P31432
|
FINISHED |
| Object | Imperial Germany |
—
|
NE NERFINISHED |
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: Imperial Germany | Statement: [Max von Boehn, hasCitizenshipDuringActivity, Imperial Germany]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCitizenshipDuringActivity Context triple: [Max von Boehn, hasCitizenshipDuringActivity, Imperial Germany]
-
A.
citizenshipDuringLifetime
chosen
Indicates that an entity held citizenship in a particular country or political unit at some point during its lifetime.
-
B.
citizenshipDuringCompetition
Indicates that an individual held a particular citizenship status during the time a specified competition took place.
-
C.
hasHostCitizenship
Indicates that an entity holds citizenship in, or is a citizen of, a specified host country or jurisdiction.
-
D.
hasTypicalCitizenship
Indicates that an entity is generally or commonly a citizen of a specified country or jurisdiction.
-
E.
citizenshipStatusDuringFlight
Indicates the legal citizenship status an individual holds while they are in transit on a particular flight.
- 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_69ef52003fb48190b0f1295246182a86 |
completed | April 27, 2026, 12:09 p.m. |
| NER | Named-entity recognition | batch_69f6a28c7c148190bfc980aad9f678ca |
completed | May 3, 2026, 1:19 a.m. |
| PD | Predicate disambiguation | batch_69f69fe1e3c88190830bb2e9f407357e |
completed | May 3, 2026, 1:07 a.m. |
Created at: April 27, 2026, 12:42 p.m.