Triple
T16020664
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cèze |
E388587
|
entity |
| Predicate | hasTownOnBank |
P847
|
FINISHED |
| Object | Saint-Ambroix |
E1189131
|
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-Ambroix | Statement: [Cèze, hasTownOnBank, Saint-Ambroix]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Ambroix Context triple: [Cèze, hasTownOnBank, Saint-Ambroix]
-
A.
Saint-Ambroix
chosen
Saint-Ambroix is a small commune in southern France’s Gard department, known for its historic village center and scenic setting along the Cèze River.
-
B.
Fontaine-au-Bois
Fontaine-au-Bois is a small commune in the Nord department of northern France, situated within the administrative area of the Hauts-de-France region.
-
C.
Breteuil
Breteuil is a commune in northern France that serves as a local administrative and service hub for its surrounding rural area.
-
D.
La Croix-Valmer
La Croix-Valmer is a coastal commune on the French Riviera in the Var department of southeastern France, known for its Mediterranean beaches and proximity to Saint-Tropez.
-
E.
Cambronne
Cambronne is a Paris Métro station located in the 15th arrondissement, named after the French general Pierre Cambronne.
- 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_69d86dabcb7c8190b6a39d6831d2fa1b |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e183231f2c81908f4e4037c3aa180b |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffe47280448190923a36e9a41ce7bc |
completed | May 10, 2026, 1:50 a.m. |
Created at: April 10, 2026, 4:55 a.m.