Triple
T15202753
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Papal election of 1352 |
E363307
|
entity |
| Predicate | electedPersonNationality |
P17302
|
FINISHED |
| Object | French |
—
|
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: French | Statement: [Papal election of 1352, electedPersonNationality, French]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: electedPersonNationality Context triple: [Papal election of 1352, electedPersonNationality, French]
-
A.
officeHolderNationality
chosen
Indicates that the nationality of an office holder is a specified country or nation.
-
B.
leaderNationality
Indicates that a leader has a specific national affiliation or citizenship.
-
C.
notableMemberNationality
Indicates that the notable member of a group or organization has the specified nationality.
-
D.
isAmericanPolitician
Indicates that a person is a politician who holds or has held political office in the United States.
-
E.
notableOfficeHolder
Indicates that an entity is a significant or distinguished holder of a particular office or position 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_69d85a0b78bc8190b6e5ad51a2c4cfc5 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e006b693a48190a6230b7b52bc8cd3 |
completed | April 15, 2026, 9:44 p.m. |
| PD | Predicate disambiguation | batch_69deb97ee9d881908711dbe12a55283c |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:10 a.m.