Triple
T11989370
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Manezhnaya Square |
E285364
|
entity |
| Predicate | touristHub |
P33214
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Manezhnaya Square, touristHub, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristHub Context triple: [Manezhnaya Square, touristHub, true]
-
A.
touristGatewayTo
Indicates a relationship where one place serves as the primary access point or entry hub for tourists visiting another place.
-
B.
tourismFeature
chosen
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
C.
tourismRegion
Indicates that a place or area is designated or recognized as a tourism region associated with another geographic or administrative entity.
-
D.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
-
E.
touristAttractionIn
Indicates that a place functions as a tourist attraction located within a specified geographic area or entity.
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903afe4388190a2cf2328e85adf9b |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902abca70819098291aa51b593708 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.