Triple
T13217508
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joan of France |
E314657
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Valois |
E305764
|
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: Valois | Statement: [Joan of France, familyName, Valois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Valois Context triple: [Joan of France, familyName, Valois]
-
A.
Valois
chosen
Valois was a prominent French royal dynasty that ruled France during the late Middle Ages and Renaissance, succeeding the Capetians and preceding the Bourbons.
-
B.
Capet
Capet is the dynastic surname of the medieval French royal house that began with Hugh Capet and ruled France for centuries.
-
C.
Dauphine of France
The Dauphine of France was the title given to the wife of the heir apparent to the French throne, signifying her status as the kingdom’s future queen consort.
-
D.
Victoria of France
Victoria of France was a French princess, daughter of King Henry II and Catherine de' Medici, and sister of King Francis II of France.
-
E.
Francois
Francois is the given first name of South African rugby union scrum-half Faf de Klerk.
- 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_69d806affc688190a25b6ccc588e9c72 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf392e08190949ee4d194566395 |
completed | April 10, 2026, 11:51 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6ff2085f88190be8cfc309d21f9cb |
completed | May 3, 2026, 7:54 a.m. |
Created at: April 9, 2026, 9:18 p.m.