Triple
T9870614
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Quai de l’Horloge |
E239945
|
entity |
| Predicate | hasAdjacentWaterBodyUse |
P77032
|
FINISHED |
| Object | navigation on the Seine |
—
|
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: navigation on the Seine | Statement: [Quai de l’Horloge, hasAdjacentWaterBodyUse, navigation on the Seine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAdjacentWaterBodyUse Context triple: [Quai de l’Horloge, hasAdjacentWaterBodyUse, navigation on the Seine]
-
A.
hasNearbyWatersUsedBy
Indicates that a body of water located near an entity is utilized or accessed by another specified entity.
-
B.
hasNearbyWater
Indicates that one entity is located close to a body of water associated with or relevant to another entity.
-
C.
hasAssociatedWaterBody
Indicates that one entity is linked to, or occurs in connection with, a specific body of water such as a river, lake, or sea.
-
D.
hasWaterfrontUse
chosen
Indicates that an entity is used, designated, or suitable for activities or purposes directly related to a waterfront or shoreline area.
-
E.
adjacentToBodyOfWater
Indicates that one entity is directly next to or bordering a body of water, such as a lake, river, or ocean.
- 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_69ca84e7506c819095cbde4ff16512bb |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cdb3d62628819094786a49b9bcd09b |
completed | April 2, 2026, 12:09 a.m. |
| PD | Predicate disambiguation | batch_69cd1d7621d48190aa6a6f34399514b0 |
completed | April 1, 2026, 1:28 p.m. |
Created at: March 30, 2026, 8:36 p.m.