Triple
T7852127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayenne River |
E182080
|
entity |
| Predicate | flowsThroughTown |
P42402
|
FINISHED |
| Object | Laval |
E362220
|
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: Laval | Statement: [Mayenne River, flowsThroughTown, Laval]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laval Context triple: [Mayenne River, flowsThroughTown, Laval]
-
A.
Laval
chosen
Laval is a major city in western France, located in the Mayenne department, known for its historic architecture and role as an administrative and economic center of the region.
-
B.
Laval
Laval is a large suburban city and island located just north of Montreal in southwestern Quebec, Canada.
-
C.
Sherbrooke
Sherbrooke is a major city in southern Quebec, Canada, known as an important economic, cultural, and educational center in the Eastern Townships region.
-
D.
Limoilou
Limoilou is a primarily residential neighborhood in Quebec City, Canada, known for its dense urban fabric, vibrant local commerce, and historic working-class character.
-
E.
Villeneuve-le-Roi
Villeneuve-le-Roi is a suburban commune in the southeastern outskirts of Paris, France, situated along the Seine River and closely linked to the nearby Orly Airport.
- 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_69ca82869ee08190b8f9040dbc2c0467 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb18ec48548190960bd564a60effa8 |
completed | March 31, 2026, 12:44 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5b161a4881909641f3a29c1650b4 |
completed | March 31, 2026, 5:26 a.m. |
Created at: March 30, 2026, 4:51 p.m.