Triple
T619511
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | St. Nicholas Anapausas Monastery |
E14479
|
entity |
| Predicate | touristAccess |
P17187
|
FINISHED |
| Object | open to visitors with dress code |
—
|
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: open to visitors with dress code | Statement: [St. Nicholas Anapausas Monastery, touristAccess, open to visitors with dress code]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: touristAccess Context triple: [St. Nicholas Anapausas Monastery, touristAccess, open to visitors with dress code]
-
A.
tourAccess
Indicates that an entity is permitted to participate in, enter, or make use of a specific tour.
-
B.
hasTouristInfrastructure
Indicates that a place is equipped with facilities and services designed to support and accommodate tourists.
-
C.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
D.
isTouristDestination
Indicates that a place is recognized as a location people commonly visit for leisure, sightseeing, or travel.
-
E.
visitorCenter
Indicates that a location serves as a visitor center for a place, providing information or services to visitors of that place.
- F. None of above. chosen
Provenance (4 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_69a4934b17c881909ace8270e8ddd202 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e270b448190beb677670443b5b6 |
completed | March 1, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69a49cfe9bc081909a01b4b3b48f03b7 |
completed | March 1, 2026, 8:09 p.m. |
| PDg | Predicate description generation | batch_69a49def31ec81909dc53e70f4a36eda |
completed | March 1, 2026, 8:13 p.m. |
Created at: March 1, 2026, 7:35 p.m.