Triple
T7286829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hotel Inglaterra |
E163889
|
entity |
| Predicate | hasTouristRatingCategory |
P30883
|
FINISHED |
| Object | 4-star hotel |
—
|
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: 4-star hotel | Statement: [Hotel Inglaterra, hasTouristRatingCategory, 4-star hotel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristRatingCategory Context triple: [Hotel Inglaterra, hasTouristRatingCategory, 4-star hotel]
-
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.
hasTouristRank
Indicates that an entity is assigned a specific rank or rating based on its attractiveness or importance as a tourist destination.
-
C.
hasTouristPopularity
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
-
D.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
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_69c6886093b88190a254b1ce6db8bae7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6eb532adc8190bcbbf31bb54383fb |
completed | March 27, 2026, 8:40 p.m. |
| PD | Predicate disambiguation | batch_69c6e76c5fbc8190b378830082f11cb0 |
completed | March 27, 2026, 8:24 p.m. |
Created at: March 27, 2026, 2:59 p.m.