Triple
T26955531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Loire River basin |
E678890
|
entity |
| Predicate | drainageRiverLength |
P156298
|
FINISHED |
| Object | longest river in France |
—
|
LITERAL 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: longest river in France | Statement: [Loire River basin, drainageRiverLength, longest river in France]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: drainageRiverLength Context triple: [Loire River basin, drainageRiverLength, longest river in France]
-
A.
riverLength
Indicates the measured extent of a river from its source to its mouth, typically expressed as a linear distance.
-
B.
waterwayLengthKilometres
Indicates the total length of a waterway, measured in kilometres.
-
C.
riverLengthContext
chosen
Indicates the contextual or situational information under which a river’s length is measured or considered.
-
D.
undergroundRiverLength
Indicates the measured linear extent of an underground river from its starting point to its endpoint.
-
E.
hasLongestRiver
Indicates that one entity possesses or contains the river that is longer than any other river associated with the compared entities.
- F. None of above.
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_69eeeb4e75f08190b14fc91ca4a91488 |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f625411c14819086492062e86ba8d5 |
completed | May 2, 2026, 4:24 p.m. |
| PD | Predicate disambiguation | batch_69f623a91b9c8190b2e2fdbc55cb89b6 |
completed | May 2, 2026, 4:17 p.m. |
Created at: April 27, 2026, 6:27 a.m.