Triple
T2236835
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Seine River Basin |
E49299
|
entity |
| Predicate | containsLandUse |
P14072
|
FINISHED |
| Object | urban areas |
—
|
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: urban areas | Statement: [Seine River Basin, containsLandUse, urban areas]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: containsLandUse Context triple: [Seine River Basin, containsLandUse, urban areas]
-
A.
otherLandUse
Indicates that the land is used for purposes that do not fall into any of the primary or predefined land-use categories.
-
B.
primaryLandUse
chosen
Indicates the main or dominant way in which a given piece of land is utilized or designated (e.g., residential, agricultural, commercial).
-
C.
secondaryLandUse
Indicates a secondary or additional way in which a piece of land is used, beyond its primary designated use.
-
D.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
E.
hasFloodplainUse
Indicates that a floodplain area is being used or designated for a particular purpose or activity.
- 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_69a88aa84bdc819086df50e9c20b301e |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc09573848190bf91eddcc2fa0061 |
completed | March 7, 2026, 6:07 a.m. |
| PD | Predicate disambiguation | batch_69abbdafc07881909101266a33ae7031 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:47 p.m.