Triple
T9174525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Alejandra |
E220162
|
entity |
| Predicate | usageCulture |
P7826
|
FINISHED |
| Object | Spanish-speaking cultures |
—
|
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-speaking cultures | Statement: [Alejandra, usageCulture, Spanish-speaking cultures]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usageCulture Context triple: [Alejandra, usageCulture, Spanish-speaking cultures]
-
A.
usedInCulture
chosen
Indicates that something (such as an object, practice, or concept) is employed, referenced, or plays a role within a particular culture or cultural context.
-
B.
languageUse
Indicates the language or languages an entity uses for communication, expression, or interaction.
-
C.
positionOnCulture
Indicates the stance, viewpoint, or opinion that one entity holds regarding cultural issues, practices, or phenomena in relation to another entity or context.
-
D.
typicalLanguageUse
Indicates that one entity is the language most commonly or habitually used by another entity in ordinary communication or contexts.
-
E.
locale
Indicates that one entity is the place, setting, or geographic area in which another entity exists, occurs, or is situated.
- 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_69ca83e467108190abcae6a33b3d4dad |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccbfa2f9708190a955bf28a4f04004 |
completed | April 1, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:23 p.m.