Triple
T28815467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Murrisk |
E727629
|
entity |
| Predicate | tourismDrivenBy |
P146749
|
FINISHED |
| Object | pilgrimage to Croagh Patrick |
—
|
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: pilgrimage to Croagh Patrick | Statement: [Murrisk, tourismDrivenBy, pilgrimage to Croagh Patrick]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismDrivenBy Context triple: [Murrisk, tourismDrivenBy, pilgrimage to Croagh Patrick]
-
A.
tourismMotivation
chosen
Indicates the reasons or driving factors that motivate an entity (typically a person) to engage in tourism or travel activities.
-
B.
tourismBoom
Indicates a rapid and significant increase in tourism activity, such as visitor numbers, spending, or development, within a particular place or period.
-
C.
tourismType
Indicates the specific category or kind of tourism activity or experience associated with an entity.
-
D.
hadTourismEconomyFor
Indicates that an entity has sustained a tourism-based economy for a specified period or duration.
-
E.
tourismTrend
Indicates how patterns or levels of tourism activity change over time or across locations.
- 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_69f0319d09088190bbf14cdf1987792a |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f65f7731e4819099d5bd3d915ee266 |
completed | May 2, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f65c2198208190a3954086c22cfcbf |
completed | May 2, 2026, 8:18 p.m. |
Created at: April 28, 2026, 6:32 a.m.