Triple
T8423241
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madres de Plaza de Mayo marches |
E198912
|
entity |
| Predicate | languageOfBanners |
P4196
|
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: [Madres de Plaza de Mayo marches, languageOfBanners, Spanish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfBanners Context triple: [Madres de Plaza de Mayo marches, languageOfBanners, Spanish]
-
A.
languageOfTranslations
Indicates that one entity is the language into which another entity (such as a text or work) has been translated.
-
B.
languageOfOfficialAnnouncements
Indicates the language used for formal or official public announcements issued by an authority.
-
C.
languageBranch
Indicates that one language belongs to, or is classified under, a broader linguistic branch or subgroup.
-
D.
languageOfSignage
chosen
Indicates the language used on signs or written displays associated with an entity.
-
E.
serviceBrandLanguage
Indicates the language or languages in which a service brand communicates or is presented.
- 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_69ca8312d63c8190bf133b676b44a385 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cb859f787481908a11797a317c8849 |
completed | March 31, 2026, 8:28 a.m. |
| PD | Predicate disambiguation | batch_69cb70d70ea081909c3dc1bd2ec14f85 |
completed | March 31, 2026, 6:59 a.m. |
Created at: March 30, 2026, 6:06 p.m.