Triple
T12019951
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de l’Étuve / Stoofstraat |
E286121
|
entity |
| Predicate | hasTouristDensity |
P20205
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Rue de l’Étuve / Stoofstraat, hasTouristDensity, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristDensity Context triple: [Rue de l’Étuve / Stoofstraat, hasTouristDensity, high]
-
A.
hasTouristPopularity
chosen
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
-
B.
hasTouristVisits
Indicates that one entity experiences or records visits from tourists to another entity.
-
C.
containsTouristArea
Indicates that a place or region includes within its boundaries an area primarily designated or recognized for tourism activities.
-
D.
hasTouristProfile
Indicates that an entity possesses characteristics, data, or attributes defining it as a tourist or related to tourism behavior.
-
E.
isPartOfTouristArea
Indicates that one entity is located within or belongs to a designated tourist area or tourist-focused region.
- 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_69d6ab45a368819084fce08bf0dc3705 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902b6ebbc8190b13c44a61c6f81b9 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:47 p.m.