Triple
T33067662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | La Industria Inc. |
E846144
|
entity |
| Predicate | associatedLanguageMarket |
P39166
|
FINISHED |
| Object | Spanish-language music market |
—
|
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: Spanish-language music market | Statement: [La Industria Inc., associatedLanguageMarket, Spanish-language music market]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedLanguageMarket Context triple: [La Industria Inc., associatedLanguageMarket, Spanish-language music market]
-
A.
primaryLanguageMarket
Indicates that a particular language is the main or dominant language used within a given market or market segment.
-
B.
marketNameLanguage
Indicates the language in which a market’s name is expressed or recorded.
-
C.
targetsLanguage
Indicates that an action, resource, or entity is specifically directed toward, designed for, or intended to be used with a particular language.
-
D.
languageOfPrimaryMarkets
chosen
Indicates the primary language or languages used in the main markets where an entity operates or targets its products or services.
-
E.
hasLanguageOfSurroundingCountries
Indicates that an entity uses or includes the languages commonly spoken in the countries that geographically surround it.
- 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_69f3495405b88190967af2157b43b896 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f338b881908e5593e45d764f4d |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:25 a.m.