Triple
T22818327
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TSS Earnslaw |
E565158
|
entity |
| Predicate | refittedForTourism |
P149856
|
FINISHED |
| Object | 1960s |
—
|
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: 1960s | Statement: [TSS Earnslaw, refittedForTourism, 1960s]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: refittedForTourism Context triple: [TSS Earnslaw, refittedForTourism, 1960s]
-
A.
hasTourismStyle
Indicates the type or style of tourism associated with or characteristic of a particular entity.
-
B.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
C.
hasTouristInfrastructure
Indicates that a place is equipped with facilities and services designed to support and accommodate tourists.
-
D.
hasTourismPotential
Indicates that a place or resource possesses qualities that make it attractive or suitable for tourism activities or development.
-
E.
hadTourismEconomyFor
Indicates that an entity has sustained a tourism-based economy for a specified period or duration.
- 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_69e2458426188190b58b8ab4844fe420 |
completed | April 17, 2026, 2:36 p.m. |
| NER | Named-entity recognition | batch_69f17dce762c8190934fb921f942c9fd |
completed | April 29, 2026, 3:41 a.m. |
| PD | Predicate disambiguation | batch_69eed2d117088190acbfe130d84f8627 |
completed | April 27, 2026, 3:06 a.m. |
| PDg | Predicate description generation | batch_69eeeb577e2081909f4a4e9c296535c0 |
completed | April 27, 2026, 4:51 a.m. |
Created at: April 17, 2026, 3:33 p.m.