Triple
T9445436
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stresa |
E227750
|
entity |
| Predicate | hasProminentSector |
P50235
|
FINISHED |
| Object | hospitality industry |
—
|
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: hospitality industry | Statement: [Stresa, hasProminentSector, hospitality industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProminentSector Context triple: [Stresa, hasProminentSector, hospitality industry]
-
A.
hasProminentAspect
Indicates that an entity possesses a particularly notable, dominant, or emphasized aspect or feature.
-
B.
dominatedSector
Indicates that one entity exercises prevailing control or influence over a particular sector relative to others.
-
C.
hasSectoralPriority
Indicates that something is designated as having priority or special importance within a particular sector or industry.
-
D.
notableSector
chosen
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
E.
hasProminence
Indicates that one entity stands out in importance, visibility, or influence relative to others within a given context.
- 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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7f33deb88190bc74968575963ac4 |
completed | April 1, 2026, 8:25 p.m. |
| PD | Predicate disambiguation | batch_69cca5596ffc819097e9c8eefd4ef9b8 |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:51 p.m.