Triple
T37730683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Temple Newsam |
E940143
|
entity |
| Predicate | tourismAttracts |
P33524
|
FINISHED |
| Object | local visitors |
—
|
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: local visitors | Statement: [Temple Newsam, tourismAttracts, local visitors]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tourismAttracts Context triple: [Temple Newsam, tourismAttracts, local visitors]
-
A.
tourismFeature
Indicates that something serves as an attraction, amenity, or point of interest relevant to tourism or visitors.
-
B.
tourismCharacteristic
Indicates that something has a specific feature, quality, or attribute relevant to tourism, such as what makes a place, service, or activity notable or suitable for tourists.
-
C.
tourismDraw
chosen
Indicates that one entity attracts tourists or visitor interest to another entity or location.
-
D.
alsoAttractsTouristsIn
Indicates that a place, in addition to another, draws or appeals to tourists within a specified location or context.
-
E.
tourismFrom
Indicates that tourists or visitor activity originates from one place and is directed toward another location.
- 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_69f76edefd048190a32212c5c3919531 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_69fbaef0cec881908c2742d77d145901 |
completed | May 6, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69fbadf632ec8190b14991c971258307 |
completed | May 6, 2026, 9:09 p.m. |
Created at: May 3, 2026, 4:18 p.m.