Triple
T26026143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cason |
E647295
|
entity |
| Predicate | relatedNamingTrend |
P39078
|
FINISHED |
| Object | surname-style first names |
—
|
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: surname-style first names | Statement: [Cason, relatedNamingTrend, surname-style first names]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relatedNamingTrend Context triple: [Cason, relatedNamingTrend, surname-style first names]
-
A.
hasTrend
Indicates that something exhibits or is associated with a particular pattern of change or direction over time.
-
B.
socialMediaTrend
Indicates that something is currently popular, widely discussed, or rapidly spreading in visibility and engagement on social media platforms.
-
C.
trends
chosen
Indicates that one entity exhibits a general direction of change or development over time in relation to another reference or context.
-
D.
languageUseTrend
Indicates how the use or prevalence of a particular language changes over time within a given population or context.
-
E.
nationalPopularity
Indicates the degree to which something is liked, recognized, or supported by people across an entire nation.
- 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_69e77e8b60e88190a3b26c4f0032a2c2 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69fda5003cdc8190a558501271389912 |
completed | May 8, 2026, 8:55 a.m. |
| PD | Predicate disambiguation | batch_69fda05bfc2c819096821a5300e9bb24 |
completed | May 8, 2026, 8:35 a.m. |
Created at: April 22, 2026, 9:05 a.m.