Triple
T22530776
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fère-en-Tardenois |
E557028
|
entity |
| Predicate | hasHistoricRegion |
P5057
|
FINISHED |
| Object | Tardenois |
—
|
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: Tardenois | Statement: [Fère-en-Tardenois, hasHistoricRegion, Tardenois]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tardenois Context triple: [Fère-en-Tardenois, hasHistoricRegion, Tardenois]
-
A.
Tardenois plateau
chosen
The Tardenois plateau is a gently rolling upland region in northern France known for its agricultural landscapes and its role as a World War I battlefield area.
-
B.
Picardy plateau
The Picardy plateau is a broad, gently undulating lowland region in northern France characterized by fertile agricultural land and open landscapes.
-
C.
Plaine de France
Plaine de France is a fertile agricultural plain and historical region in northern Île-de-France, just north of Paris.
-
D.
Morvan
Morvan is a character in Samuel Beckett’s short play "Rough for Theatre II," typically portrayed as one of two bureaucrats coldly evaluating a man’s life from his personal documents.
-
E.
Souain
Souain is a commune in the Marne department of northeastern France, known for its World War I battlefields and memorials.
- 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_69e11e57483c8190b0887c4f8ff26446 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15ed6734881908abbbee477dfab98 |
completed | April 29, 2026, 1:28 a.m. |
Created at: April 16, 2026, 8:51 p.m.