Triple
T31345518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aasee (Münster) |
E799436
|
entity |
| Predicate | shoreHasFacility |
P85723
|
FINISHED |
| Object | restaurants |
—
|
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: restaurants | Statement: [Aasee (Münster), shoreHasFacility, restaurants]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shoreHasFacility Context triple: [Aasee (Münster), shoreHasFacility, restaurants]
-
A.
shoreHas
chosen
Indicates that a shore possesses, contains, or is characterized by a particular feature, object, or attribute.
-
B.
hasSeaAccess
Indicates that an entity has direct access to the sea, typically via a coastline, port, or navigable waterway connected to the sea.
-
C.
hasStructureOnShore
Indicates that a structure is located on or directly adjacent to the shore of a body of water.
-
D.
shoreType
Indicates the kind or classification of a shoreline associated with a body of water or coastal area.
-
E.
hasWaterfrontAccessTo
Indicates that one entity is directly adjacent to and can physically access a particular 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_69f224e51614819083141459a080e97c |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f69f17e9108190acbfc5367250f405 |
completed | May 3, 2026, 1:04 a.m. |
| PD | Predicate disambiguation | batch_69f69d1d25e88190a7f57d323574da90 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 29, 2026, 9:17 p.m.