Triple
T3375694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Stephen's Basilica |
E71060
|
entity |
| Predicate | touristImportance |
P7889
|
FINISHED |
| Object | major tourist attraction in Budapest |
—
|
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: major tourist attraction in Budapest | Statement: [St. Stephen's Basilica, touristImportance, major tourist attraction in Budapest]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristImportance Context triple: [St. Stephen's Basilica, touristImportance, major tourist attraction in Budapest]
-
A.
tourismImportance
chosen
Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
-
B.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
C.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
D.
hasTourismImpactOn
Indicates that one entity affects or influences the tourism levels, patterns, or attractiveness of another entity.
-
E.
hasTouristPopularity
Indicates that a place or attraction is recognized as being popular or frequently visited by tourists.
- 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_69ad85a7f80c8190a05e43013f298942 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb2e5fc6c81909ff582611751096d |
completed | March 8, 2026, 5:33 p.m. |
| PD | Predicate disambiguation | batch_69ada433059881908e46f38cc5f40a32 |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:13 p.m.