Triple
T11888317
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henri II de Bourbon, Prince de Condé |
E282848
|
entity |
| Predicate | birthPlace |
P1
|
FINISHED |
| Object | Saint-Jean-d’Angély |
E622910
|
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: Saint-Jean-d’Angély | Statement: [Henri II de Bourbon, Prince de Condé, birthPlace, Saint-Jean-d’Angély]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Jean-d’Angély Context triple: [Henri II de Bourbon, Prince de Condé, birthPlace, Saint-Jean-d’Angély]
-
A.
Saint-Jean-d’Angély
chosen
Saint-Jean-d’Angély is a historic market town in southwestern France, noted for its medieval architecture and former royal abbey on the pilgrimage route to Santiago de Compostela.
-
B.
Rochefort
Rochefort is a town in the Walloon region of Belgium, known for its historic abbey and Trappist beer.
-
C.
Rochefort
Rochefort is a historic French port town on the Atlantic coast known for its naval heritage and maritime museum sites.
-
D.
Rochefort
Rochefort is a municipality in the canton of Neuchâtel in western Switzerland.
-
E.
Saintes
Saintes is a historic town in southwestern France, known for its well-preserved Roman and medieval heritage, including ancient monuments and religious sites.
- 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_69d6ab2a90b08190a4e818821cc93e6d |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d3a2860c8190a21af5fcddbd2f1e |
completed | April 10, 2026, 10:40 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f417e919548190acbc248879f957ec |
completed | May 1, 2026, 3:03 a.m. |
Created at: April 8, 2026, 9:44 p.m.