Triple
T3911506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canton of Saint-Genis-Pouilly |
E87330
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Farges |
E341372
|
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: Farges | Statement: [Canton of Saint-Genis-Pouilly, contains, Farges]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Farges Context triple: [Canton of Saint-Genis-Pouilly, contains, Farges]
-
A.
Farges
chosen
Farges is a small commune in eastern France, located in the Ain department near the Swiss border in the Auvergne-Rhône-Alpes region.
-
B.
Faya-Largeau
Faya-Largeau is the largest oasis town in northern Chad and an important administrative and trade center in the Sahara Desert.
-
C.
Gressy
Gressy is a small French commune located in the Île-de-France region, known for its residential character and proximity to Paris and Charles de Gaulle Airport.
-
D.
Boissière
Boissière is a Paris Métro station on the city’s Right Bank, located in the 16th arrondissement near the Trocadéro area.
-
E.
Breuillet
Breuillet is a commune in the Essonne department in the Île-de-France region of northern France.
- 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_69aed9424514819086e9c58adde6652d |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aeed35e2d081908b5d87c7630e7ffc |
completed | March 9, 2026, 3:54 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5285851248190a18cea371aacbc49 |
completed | March 14, 2026, 9:20 a.m. |
Created at: March 9, 2026, 3:22 p.m.