Triple
T12183605
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plaza Sésamo |
E290277
|
entity |
| Predicate | hasLocalizedContent |
P83197
|
FINISHED |
| Object | Mexican culture |
—
|
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: Mexican culture | Statement: [Plaza Sésamo, hasLocalizedContent, Mexican culture]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLocalizedContent Context triple: [Plaza Sésamo, hasLocalizedContent, Mexican culture]
-
A.
isLocalizable
Indicates that something can be adapted or translated to different languages or locales without losing its intended function or meaning.
-
B.
languageOfLocalization
Indicates the language into which something (such as software, content, or an interface) has been localized for use or display.
-
C.
hasTranslation
Indicates that one entity is a translation or translated version of another entity in a different language.
-
D.
hasLocalCharacter
Indicates that something possesses qualities, features, or significance that are specific to a particular locality or region.
-
E.
hasContentTailoredTo
chosen
Indicates that something (such as a message, product, or experience) has its content specifically adapted or customized to suit a particular target, context, or audience.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91a83012c81908d04bbab5fdcd8c2 |
completed | April 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69d91510a258819090ef8fbdc2d8707b |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.