Triple
T23326372
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Love |
E591302
|
entity |
| Predicate | hasCulturalVariationIn |
P8516
|
FINISHED |
| Object | expression |
—
|
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: expression | Statement: [Love, hasCulturalVariationIn, expression]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCulturalVariationIn Context triple: [Love, hasCulturalVariationIn, expression]
-
A.
culturalVariation
chosen
Indicates that there are differences in practices, beliefs, or expressions between cultures or within a culture across groups, contexts, or time.
-
B.
hasRegionalVariationsIn
Indicates that something exhibits different forms, versions, or characteristics depending on the geographic region.
-
C.
hasCulturalAdaptation
Indicates that one entity has been modified, interpreted, or re-created to fit the cultural context, norms, or preferences of another entity or audience.
-
D.
isCulturalDistinction
Indicates that one entity is recognized as a distinguishing cultural feature or marker in comparison to another entity or context.
-
E.
hasCulturalEquivalent
Indicates that one entity has a counterpart in another cultural context that plays a similar role, function, or meaning.
- 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_69e25d1effe4819096907f95f610dbff |
completed | April 17, 2026, 4:17 p.m. |
| NER | Named-entity recognition | batch_69f197eaa7b88190aad2096c110dadea |
completed | April 29, 2026, 5:32 a.m. |
| PD | Predicate disambiguation | batch_69effcf8ca2c8190887d4f4656617d21 |
completed | April 28, 2026, 12:19 a.m. |
Created at: April 17, 2026, 5:12 p.m.