Triple
T28272106
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Villa Independencia |
E712884
|
entity |
| Predicate | associatedWithIndustryType |
P47404
|
FINISHED |
| Object | food 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: food industry | Statement: [Villa Independencia, associatedWithIndustryType, food industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithIndustryType Context triple: [Villa Independencia, associatedWithIndustryType, food industry]
-
A.
isAssociatedWithIssuerIndustry
Indicates that an entity has a relationship or connection to the industry in which the issuer operates.
-
B.
associatedWorkType
Indicates the type or category of work with which an entity is associated (e.g., publication, artwork, performance).
-
C.
majorIndustryAssociation
Indicates that there is a significant or primary industry-related association or affiliation between the entities.
-
D.
relationToIndustry
chosen
Indicates how an entity is connected or relevant to a particular industry, such as through involvement, impact, or association.
-
E.
associatedWithCareerOf
Indicates a relationship where something is connected or relevant to a person’s professional life, occupation, or career trajectory.
- 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_69efb5216c6881908020dce4aea65381 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_6a0119132e848190820a688d139fbf75 |
completed | May 10, 2026, 11:47 p.m. |
| PD | Predicate disambiguation | batch_6a01188dfdec8190b7f675264a281733 |
completed | May 10, 2026, 11:45 p.m. |
Created at: April 27, 2026, 11:18 p.m.