Triple
T27017238
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verbanesi |
E680567
|
entity |
| Predicate | associatedWithEconomySector |
P47145
|
FINISHED |
| Object | tourism |
—
|
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: tourism | Statement: [Verbanesi, associatedWithEconomySector, tourism]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithEconomySector Context triple: [Verbanesi, associatedWithEconomySector, tourism]
-
A.
associatedWithEconomicSector
chosen
Indicates that an entity has a connection or involvement with a particular economic sector, such as operating, participating, or being relevant within that sector.
-
B.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
C.
ownerSector
Indicates the sector or industry category to which the owner of an entity belongs.
-
D.
sectoralClassification
Indicates how an entity is categorized into a specific economic or industry sector within a classification scheme.
-
E.
isPartOfEconomicCluster
Indicates that an entity belongs to, or is included within, a larger economic cluster or grouping based on economic relationships or activities.
- 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_69eeeb5450988190bfc9a3c012ac463a |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69ff9a25407c81909faa86e72a7a9d17 |
completed | May 9, 2026, 8:33 p.m. |
| PD | Predicate disambiguation | batch_69ff99c613688190a03b2f93d5ccad2b |
completed | May 9, 2026, 8:32 p.m. |
Created at: April 27, 2026, 7:06 a.m.