Triple
T14949676
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mayenne |
E372757
|
entity |
| Predicate | administrativeCenter |
P1474
|
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, administrativeCenter, Laval]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Laval Context triple: [Mayenne, administrativeCenter, 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.
Laval
Laval is a French surname most notably associated with Pierre Laval, a prominent and controversial political figure during the Vichy regime in World War II.
-
D.
Sherbrooke
Sherbrooke is a major city in southern Quebec, Canada, known as an important economic, cultural, and educational center in the Eastern Townships region.
-
E.
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.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68fae3c81909873b113bfcaca05 |
completed | April 15, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe8bd871188190afcba3be94dbfa94 |
completed | May 9, 2026, 1:20 a.m. |
Created at: April 10, 2026, 2:39 a.m.