Triple
T13070409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint Ludger |
E329440
|
entity |
| Predicate | countryOfCitizenship |
P2
|
FINISHED |
| Object | Francia |
E861
|
NE 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: Francia | Statement: [Saint Ludger, countryOfCitizenship, Francia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Francia Context triple: [Saint Ludger, countryOfCitizenship, Francia]
-
A.
Francia
Francia is the surname of American rower and two-time Olympic gold medalist Susan Francia.
-
B.
France
chosen
France is a major Western European nation known for its influential history, culture, and economy, and as a founding member of the European Union and the United Nations.
-
C.
Francie
Francie is a diminutive given name, typically used as a nickname for Francis or Frances.
-
D.
Pays Royannais
Pays Royannais is a coastal area in southwestern France centered around the town of Royan, known for its seaside resorts and Atlantic beaches.
-
E.
France 5
France 5 is a French public television channel known for its focus on educational, cultural, and documentary programming.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d80771749c81909a6d9197b9504872 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69d980ee6130819095d835e7ff6a8c5b |
completed | April 10, 2026, 10:59 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ead460908190a566f5416e456aeb |
completed | May 3, 2026, 6:27 a.m. |
Created at: April 9, 2026, 9 p.m.