Triple
T6204787
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madrid Deep Space Communications Complex |
E138719
|
entity |
| Predicate | languageOfLocalOperations |
P51016
|
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: [Madrid Deep Space Communications Complex, languageOfLocalOperations, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfLocalOperations Context triple: [Madrid Deep Space Communications Complex, languageOfLocalOperations, Spanish]
-
A.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
B.
tertiaryLanguageOfOperation
Indicates that an entity uses a specified language as its third most prominent or prioritized language of operation.
-
C.
languageOfLocalOrganization
chosen
Indicates the language used or officially adopted by a local organization in its operations or communications.
-
D.
languageOfEnvironment
Indicates the language predominantly used or present in a given environment or context.
-
E.
languageOfInterface
Indicates the language used by or presented in a user interface.
- 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_69c008acbea48190991c6b834bb45d65 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0626d96ec8190816c00c44668177d |
completed | March 22, 2026, 9:43 p.m. |
| PD | Predicate disambiguation | batch_69c055fdea3c81908f5d910f0d36234a |
completed | March 22, 2026, 8:50 p.m. |
Created at: March 22, 2026, 4:20 p.m.