Triple
T15347298
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Yeni Mosque |
E366955
|
entity |
| Predicate | hasTouristicValue |
P94116
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Yeni Mosque, hasTouristicValue, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTouristicValue Context triple: [Yeni Mosque, hasTouristicValue, yes]
-
A.
hasTourismPotential
chosen
Indicates that a place or resource possesses qualities that make it attractive or suitable for tourism activities or development.
-
B.
hasTourismFunction
Indicates that an entity serves a role or purpose related to tourism, such as attracting, accommodating, or providing services to tourists.
-
C.
hasTourismStyle
Indicates the type or style of tourism associated with or characteristic of a particular entity.
-
D.
hasTourismResource
Indicates that a place, area, or entity possesses or is associated with a tourism-related resource, attraction, or facility.
-
E.
hasScenicValue
Indicates that something possesses notable aesthetic or visual appeal, often due to its natural beauty or pleasing surroundings.
- 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_69d85a1355608190a6673ddb67231d54 |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e03e1749bc8190a8b9cbcb27288a5b |
completed | April 16, 2026, 1:40 a.m. |
| PD | Predicate disambiguation | batch_69deca991e5081908b0df3d1ee7d5338 |
completed | April 14, 2026, 11:15 p.m. |
Created at: April 10, 2026, 3:17 a.m.