Triple
T1492274
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Versoix |
E29605
|
entity |
| Predicate | hasLakesidePromenades |
P19053
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Versoix, hasLakesidePromenades, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakesidePromenades Context triple: [Versoix, hasLakesidePromenades, true]
-
A.
hasPromenade
Indicates that one entity features or includes a promenade, typically as a designated walkway or leisure area associated with it.
-
B.
hasWaterfrontArea
chosen
Indicates that an entity possesses or includes an area directly adjacent to or bordering a body of water.
-
C.
hasLagoon
Indicates that one entity possesses, contains, or is characterized by a lagoon in relation to another entity or location.
-
D.
hasNearbyLake
Indicates that one entity is located close to or in the vicinity of a lake.
-
E.
hasRecreationalArea
Indicates that an entity includes, provides, or is associated with a designated space intended for leisure or recreational activities.
- 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_69a498dba1d8819093b46a3a8d2485f1 |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6c4f0c88190a97ba4910c1a5d85 |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c48902808190a8028d359bcf123e |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.