Triple
T15401738
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | University of Technology of Troyes |
E368335
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Aube |
E43606
|
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: Aube | Statement: [University of Technology of Troyes, locatedIn, Aube]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Aube Context triple: [University of Technology of Troyes, locatedIn, Aube]
-
A.
Aube
chosen
Aube is a department in northeastern France known for its historic towns, Champagne vineyards, and rural landscapes.
-
B.
Aube River
The Aube River is a major waterway in northeastern France that flows through the Champagne region before joining the Seine.
-
C.
Thiérache
Thiérache is a rural, historically fortified region in northern France known for its bocage landscapes, brick churches, and traditional dairy production.
-
D.
Val-d'Oise
Val-d'Oise is a department in northern France that forms part of the Paris metropolitan region and includes both suburban areas and rural landscapes.
-
E.
Vosgien
Vosgien is a regional dialect of the Lorrain language spoken in the Vosges area of northeastern 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_69d85a16c68c819099c1b547fbc87b32 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e8ea0ac8190a5c68b1951ad3db1 |
completed | April 16, 2026, 1:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff13584f8881908b2527c51f85ae28 |
completed | May 9, 2026, 10:58 a.m. |
Created at: April 10, 2026, 3:19 a.m.