Triple
T22589935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Napoleon, King of Rome |
E564915
|
entity |
| Predicate | laterNationalityContext |
P8495
|
FINISHED |
| Object | Austrian subject |
—
|
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: Austrian subject | Statement: [Napoleon, King of Rome, laterNationalityContext, Austrian subject]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: laterNationalityContext Context triple: [Napoleon, King of Rome, laterNationalityContext, Austrian subject]
-
A.
nationalityAfterEmigration
Indicates the nationality a person acquires or holds after emigrating from their original country.
-
B.
namedAfterCountryOfCitizenship
Indicates that something is named after the country where a person holds citizenship.
-
C.
nationalityDuringLife
Indicates that a person held a particular nationality for some or all of their lifetime.
-
D.
formerCitizenship
Indicates that an entity previously held, but no longer holds, citizenship in a specified country or state.
-
E.
laterCitizenship
chosen
Indicates that an entity acquired citizenship in a country or polity at a later point in time, after some earlier status or affiliation.
- 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_69e245836014819091b91ed3074742a3 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f1615f63788190acf776b313f0794a |
completed | April 29, 2026, 1:39 a.m. |
| PD | Predicate disambiguation | batch_69ee627be4248190889a88764624e174 |
completed | April 26, 2026, 7:07 p.m. |
Created at: April 17, 2026, 2:48 p.m.