Triple
T6241388
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fulk III Nerra |
E139609
|
entity |
| Predicate | placeOfBirth |
P1
|
FINISHED |
| Object | Anjou |
E24104
|
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: Anjou | Statement: [Fulk III Nerra, placeOfBirth, Anjou]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Anjou Context triple: [Fulk III Nerra, placeOfBirth, Anjou]
-
A.
Anjou
chosen
Anjou is a historic region in western France that was once a powerful medieval county and later a duchy, playing a central role in the Angevin Empire and European dynastic politics.
-
B.
Anjou
Anjou is a residential borough in the eastern part of Montreal, Quebec, known for its suburban character and shopping centers.
-
C.
Anjou AOC
Anjou AOC is a French wine appellation in the Loire Valley known for producing a wide range of red, white, and rosé wines, including the famous Rosé d’Anjou.
-
D.
Marmande
Marmande is a town in southwestern France known for its agricultural production, particularly tomatoes, and its location in the Garonne River valley.
-
E.
Auberjonois
Auberjonois is a surname most prominently associated with René Auberjonois, an American actor known for roles in film, television, and voice work.
- 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_69c008b1c5088190ae6de2555fc05ad8 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0630797f88190a5571f6000ba2e3b |
completed | March 22, 2026, 9:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c20e07bff8819091ca881c9b4daaf6 |
completed | March 24, 2026, 4:07 a.m. |
Created at: March 22, 2026, 4:23 p.m.