Triple
T19510030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Saint-Fons |
E488123
|
entity |
| Predicate | hasDemonym |
P191
|
FINISHED |
| Object | Saint-Foniard |
—
|
NE NERFINISHED |
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-Foniard | Statement: [Saint-Fons, hasDemonym, Saint-Foniard]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Saint-Foniard Context triple: [Saint-Fons, hasDemonym, Saint-Foniard]
-
A.
Saint-Fons
chosen
Saint-Fons is a suburban commune in eastern France located just southeast of central Lyon within its metropolitan area.
-
B.
Saint-Floret
Saint-Floret is a small commune in central France’s Puy-de-Dôme department, known for its medieval heritage and picturesque setting in the Auvergne region.
-
C.
Ferrière
Ferrière is a French-language surname of Swiss origin borne by various notable individuals, including social worker and humanitarian Suzanne Ferrière.
-
D.
Villefontaine
Villefontaine is a commune in the Isère department of southeastern France, known as a suburban town within the Grenoble urban area.
-
E.
Faya-Largeau
Faya-Largeau is the largest oasis town in northern Chad and an important administrative and trade center in the Sahara Desert.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8e8d9d1c88190b01cd78b8be49384 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e6351547e481909a875bba40651094 |
completed | April 20, 2026, 2:15 p.m. |
Created at: April 10, 2026, 1:40 p.m.