Triple
T14048762
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Agta languages |
E338027
|
entity |
| Predicate | haveSmallSpeakerPopulation |
P98216
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Agta languages, haveSmallSpeakerPopulation, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveSmallSpeakerPopulation Context triple: [Agta languages, haveSmallSpeakerPopulation, true]
-
A.
haveSpeakerPopulation
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
B.
hasVerySmallResidentPopulation
Indicates that the subject location has a resident population that is extremely small in size.
-
C.
includesLanguagesWithSmallSpeakerPopulations
chosen
Indicates that something contains or covers languages spoken by relatively few people.
-
D.
isSmallDistrict
Indicates that a district is classified as small, typically based on its limited size, population, or administrative scope.
-
E.
hasSmallBodyPopulation
Indicates that an entity has a relatively low number of small celestial bodies (such as asteroids, comets, or minor planets) associated with it.
- 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_69d81c664e48819088cbd8f433aeffe5 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de3c88b5e48190b0f0149102c08992 |
completed | April 14, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69de05adef888190b023ab42ef5076b6 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 9, 2026, 10:20 p.m.