Triple
T12665325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rue de la Roquette |
E302535
|
entity |
| Predicate | hasTourismLevel |
P30883
|
FINISHED |
| Object | moderate |
—
|
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: moderate | Statement: [Rue de la Roquette, hasTourismLevel, moderate]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTourismLevel Context triple: [Rue de la Roquette, hasTourismLevel, moderate]
-
A.
hasTourismRating
chosen
Indicates that an entity has been assigned a specific tourism-related quality or rating, reflecting its appeal or suitability for tourists.
-
B.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
C.
hasTourismResource
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
D.
hasTouristRank
Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
-
E.
hasTourismPotential
Indicates that a place or resource possesses qualities that make it attractive or suitable for tourism activities or development.
- 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_69d7bded71a88190bb76e2413af9ea66 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d9617e030881908444743b8a7e0d75 |
completed | April 10, 2026, 8:45 p.m. |
| PD | Predicate disambiguation | batch_69d960b78ce8819091f15dd5013e6da5 |
completed | April 10, 2026, 8:42 p.m. |
Created at: April 9, 2026, 5:19 p.m.