Triple
T34292583
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goura |
E879930
|
entity |
| Predicate | travelInterest |
P61794
|
FINISHED |
| Object | cultural heritage |
—
|
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: cultural heritage | Statement: [Goura, travelInterest, cultural heritage]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelInterest Context triple: [Goura, travelInterest, cultural heritage]
-
A.
travelScope
Indicates the extent or range within which travel is allowed, intended, or applicable for an entity or activity.
-
B.
travelStyle
Indicates the manner or characteristic way in which an entity typically travels or undertakes journeys.
-
C.
travelZone
Indicates a relationship where an entity is located in, moves within, or is permitted to move within a specified geographic or regulatory area.
-
D.
tourismRegion
Indicates that a place or area is designated or recognized as a tourism region associated with another geographic or administrative entity.
-
E.
culturalInterest
chosen
Indicates a relationship where one entity has an interest in, appreciation for, or engagement with the culture, traditions, or cultural expressions associated with another entity.
- 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_69f349b6df1c81908e5e5b6c2ab6409b |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f72ad38a208190b4bdc828297f86ad |
completed | May 3, 2026, 11 a.m. |
| PD | Predicate disambiguation | batch_69f72a0243988190a43b8ea22457cd30 |
completed | May 3, 2026, 10:57 a.m. |
Created at: May 1, 2026, 1:57 a.m.