Triple
T8951506
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ixcatec language |
E213359
|
entity |
| Predicate | ageProfileOfSpeakers |
P76657
|
FINISHED |
| Object | mostly older adults |
—
|
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: mostly older adults | Statement: [Ixcatec language, ageProfileOfSpeakers, mostly older adults]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ageProfileOfSpeakers Context triple: [Ixcatec language, ageProfileOfSpeakers, mostly older adults]
-
A.
primarySpeakersAgeGroup
chosen
Indicates the age range category to which the main or primary speakers in a context belong.
-
B.
audienceComposition
Indicates the makeup or distribution of different groups or segments within an audience in relation to something.
-
C.
haveSpeakerPopulation
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
D.
ageGroup
Indicates the categorical age range or bracket to which an entity belongs.
-
E.
ageRange
Indicates the span of ages within which an entity or relationship is considered valid or applicable.
- 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_69ca839843408190a39069a029a89f15 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc670dc0c88190b1f59e96ad88e4ee |
completed | April 1, 2026, 12:30 a.m. |
| PD | Predicate disambiguation | batch_69cc5ed74d288190b712d739805579dc |
completed | March 31, 2026, 11:55 p.m. |
Created at: March 30, 2026, 6:59 p.m.