Triple
T18331638
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodrich-Euzkadi |
E439155
|
entity |
| Predicate | languageOfCorporateEnvironment |
P54642
|
FINISHED |
| Object | Spanish |
—
|
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 | Statement: [Goodrich-Euzkadi, languageOfCorporateEnvironment, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfCorporateEnvironment Context triple: [Goodrich-Euzkadi, languageOfCorporateEnvironment, Spanish]
-
A.
languageWithinWork
Indicates that a specific language is used or contained within a particular work (such as a document, publication, or creative piece).
-
B.
languageOfCommunications
Indicates that a specified language is used as the medium for communications associated with an entity or interaction.
-
C.
primaryLanguageInWork
Indicates that a specified language is the main or predominant language used within a particular work (such as a book, film, or document).
-
D.
languageOfInstitutionalContext
chosen
Indicates the language used as the primary medium of communication within an institutional setting or context.
-
E.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or 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_69d8b9175fec8190af865699b4e64d8c |
completed | April 10, 2026, 8:47 a.m. |
| NER | Named-entity recognition | batch_69e50eca08388190b4e757a5f63b5d41 |
completed | April 19, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69e44fe91bc08190906518e1b120fcf0 |
completed | April 19, 2026, 3:45 a.m. |
Created at: April 10, 2026, 10:36 a.m.