Triple
T5334984
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hall of Mirrors (Royal Palace of Madrid) |
E123804
|
entity |
| Predicate | tourismUse |
P1769
|
FINISHED |
| Object | guided palace tours |
—
|
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: guided palace tours | Statement: [Hall of Mirrors (Royal Palace of Madrid), tourismUse, guided palace tours]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismUse Context triple: [Hall of Mirrors (Royal Palace of Madrid), tourismUse, guided palace tours]
-
A.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
B.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
-
C.
tourismTheme
Indicates the main subject or focus of a tourism-related activity, service, or destination (such as cultural, adventure, or eco-tourism).
-
D.
tourismImportance
Indicates the degree to which a place or entity is significant or valuable as a destination or attraction for tourists.
-
E.
tourismType
chosen
Indicates the specific category or kind of tourism activity or experience associated with an 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85af799081909ee60bfbb65149ee |
completed | March 20, 2026, 5:36 p.m. |
| PD | Predicate disambiguation | batch_69bd84583dbc819088a03e3afb30178c |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.