Triple
T34748767
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | East Shewa |
E1001709
|
entity |
| Predicate | hasTownWithResortIndustry |
P37588
|
FINISHED |
| Object | Bishoftu |
—
|
NE NERFINISHED |
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: Bishoftu | Statement: [East Shewa, hasTownWithResortIndustry, Bishoftu]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTownWithResortIndustry Context triple: [East Shewa, hasTownWithResortIndustry, Bishoftu]
-
A.
isResortTown
chosen
Indicates that a town functions primarily as a resort destination, typically focused on tourism, leisure, and vacation activities.
-
B.
hasSpaTown
Indicates that a place is associated with or contains a town known for its spa or therapeutic bathing facilities.
-
C.
hasTourismIndustry
Indicates that a place or region possesses an established tourism industry, involving organized services and activities catering to visitors and travelers.
-
D.
hasPopularResort
Indicates that a location or area contains or is associated with a resort that is widely visited or well-liked.
-
E.
hasResortCommunity
Indicates that one entity includes, contains, or is associated with a resort-style residential or vacation community.
- 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_69f76db0367081909b57c50a7fb03025 |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd35d108908190b79b1e8e6bbd62aa |
completed | May 8, 2026, 1:01 a.m. |
| PD | Predicate disambiguation | batch_69fd34cb46108190b43c3b7f67ec4cd4 |
completed | May 8, 2026, 12:56 a.m. |
Created at: May 3, 2026, 3:59 p.m.