Triple
T34244873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Canovelles |
E878568
|
entity |
| Predicate | economicSphereOf |
P167311
|
FINISHED |
| Object | Barcelona |
—
|
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: Barcelona | Statement: [Canovelles, economicSphereOf, Barcelona]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicSphereOf Context triple: [Canovelles, economicSphereOf, Barcelona]
-
A.
economicScope
chosen
Indicates the range or extent of economic activities, impacts, or considerations that a given entity, action, or relationship encompasses.
-
B.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
C.
economicExtensionOf
Indicates that one entity’s economy is heavily dependent on, controlled by, or functions as an outgrowth of another entity’s economic system.
-
D.
economicSectors
Indicates a relationship that associates entities with the economic sectors or industries in which they operate or to which they belong.
-
E.
economicFunction
Indicates the role or purpose an entity serves within an economic system, such as how it contributes to production, distribution, or consumption of goods and services.
- 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_69f349b3618481909df955b063f305b2 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
Created at: May 1, 2026, 1:56 a.m.