Triple
T17424178
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Route nationale 20 |
E423693
|
entity |
| Predicate | passesThroughDepartment |
P78707
|
FINISHED |
| Object | Lot |
—
|
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: Lot | Statement: [Route nationale 20, passesThroughDepartment, Lot]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lot Context triple: [Route nationale 20, passesThroughDepartment, Lot]
-
A.
Lot
Lot is a prophet in the Abrahamic tradition known for preaching against the immoral practices of his people and for the divine destruction of the cities of Sodom and Gomorrah.
-
B.
Lot
Lot is a river in southwestern France known for flowing through scenic valleys and historic towns before joining the Garonne.
-
C.
Lot
chosen
Lot is a department in southwestern France known for its picturesque river valleys, medieval villages, and prehistoric cave art.
-
D.
LOT
LOT is the national flag carrier airline of Poland, headquartered in Warsaw and operating an extensive network of domestic and international flights.
-
E.
Land
Land is a municipality in Innlandet county, Norway, known for its rural landscapes and proximity to Randsfjorden.
- 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_69d889d88b6081908bada047f5b3ba51 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e4423999ac81909fdbd8bcffcb30c9 |
completed | April 19, 2026, 2:47 a.m. |
Created at: April 10, 2026, 5:46 a.m.