Triple
T7377829
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kunigami |
E170170
|
entity |
| Predicate | primarySpeakersAgeGroup |
P76657
|
FINISHED |
| Object | older generations |
—
|
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: older generations | Statement: [Kunigami, primarySpeakersAgeGroup, older generations]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: primarySpeakersAgeGroup Context triple: [Kunigami, primarySpeakersAgeGroup, older generations]
-
A.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
B.
primarySpeakers
Indicates the entities that are the main or most significant speakers associated with another entity (such as an event, recording, or language).
-
C.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
-
D.
attractsAgeGroup
Indicates that something tends to draw interest or appeal from people belonging to a particular age group.
-
E.
typicalAudience
Indicates the group of people for whom something (such as a work, product, or resource) is primarily intended or most suitable.
- F. None of above. chosen
Provenance (4 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_69c68a5bfaac81909ce7f001dfb70c76 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f1aa12888190b81e37b9fcd2adc0 |
completed | March 27, 2026, 9:07 p.m. |
| PD | Predicate disambiguation | batch_69c6f02ee3e08190a7a00c981129b22c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f0ebf9c88190af5a4d87d3fd338a |
completed | March 27, 2026, 9:04 p.m. |
Created at: March 27, 2026, 3:08 p.m.