Triple
T14672325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fontenoy, Wallonia, Belgium |
E344543
|
entity |
| Predicate | hasNameInDutch |
P13254
|
FINISHED |
| Object | Fontenoy |
E1161206
|
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: Fontenoy | Statement: [Fontenoy, Wallonia, Belgium, hasNameInDutch, Fontenoy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Fontenoy Context triple: [Fontenoy, Wallonia, Belgium, hasNameInDutch, Fontenoy]
-
A.
Fontenoy
chosen
Fontenoy is a village in the Walloon region of Belgium, historically notable as the site of the 1745 Battle of Fontenoy during the War of the Austrian Succession.
-
B.
Nogent
Nogent is a commune in northeastern France located within the Haute-Marne department in the Grand Est region.
-
C.
Cazeneuve-Montaut
Cazeneuve-Montaut is a small commune in the Haute-Garonne department in southwestern France.
-
D.
Fallières
Fallières is a French surname most notably borne by Armand Fallières, who served as President of France in the early 20th century.
-
E.
Villefontaine
Villefontaine is a commune in the Isère department of southeastern France, known as a suburban town within the Grenoble urban area.
- 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_69d822e283fc8190a0e4c235cf880052 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb55064cc8190b9669d0b2da61825 |
completed | April 14, 2026, 9:44 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff3d379bc881908b7954c633787165 |
completed | May 9, 2026, 1:57 p.m. |
Created at: April 10, 2026, 1:27 a.m.