Triple
T389766
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Left Bank of the Seine |
E8855
|
entity |
| Predicate | positionRelativeToSeine |
P2409
|
FINISHED |
| Object | south bank |
—
|
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: south bank | Statement: [Left Bank of the Seine, positionRelativeToSeine, south bank]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: positionRelativeToSeine Context triple: [Left Bank of the Seine, positionRelativeToSeine, south bank]
-
A.
locatedAcrossRiverFrom
Indicates that one entity is situated on the opposite side of a river relative to another entity.
-
B.
otherMainParisAirport
Indicates that one airport serves as an alternative primary airport to another in the Paris area.
-
C.
positionOn
Indicates that one entity is located on top of or at a specific place along the surface or extent of another entity.
-
D.
locatedAlong
chosen
Indicates that one entity is situated adjacent to, or running beside, the length or course of another linear feature (such as a road, river, or railway).
-
E.
capitalCityLocatedOn
Indicates that a capital city is situated on or directly adjacent to a specific geographic feature, such as a river, coast, or lake.
- 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_69a2e7f55c60819097aff65ea2ca2832 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ec5bdc848190826701590070497b |
completed | Feb. 28, 2026, 1:23 p.m. |
| PD | Predicate disambiguation | batch_69a2e96960608190bdd342da9c5ddb5e |
completed | Feb. 28, 2026, 1:11 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.