Triple
T17378363
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ongan |
E422499
|
entity |
| Predicate | hasSpeakerPopulationCharacteristic |
P126249
|
FINISHED |
| Object | very small number of speakers |
—
|
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: very small number of speakers | Statement: [Ongan, hasSpeakerPopulationCharacteristic, very small number of speakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeakerPopulationCharacteristic Context triple: [Ongan, hasSpeakerPopulationCharacteristic, very small number of speakers]
-
A.
haveSpeakerPopulation
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
B.
hasNumberOfSpeakersCategory
chosen
Indicates a classification of an entity based on the number of speakers associated with it, typically grouping it into predefined size categories.
-
C.
hasCharacterSpeaker
Indicates that a particular character is the one who speaks or delivers the associated utterance or dialogue.
-
D.
hasSpeakerType
Indicates that an entity functions in a particular role or category as a speaker (e.g., narrator, character, announcer) within a given context.
-
E.
hasSpeakersAmong
Indicates that a group, event, or entity includes one or more speakers drawn from a specified set or category.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a840cd08190af3385388afb8c8f |
completed | April 19, 2026, 2:14 a.m. |
| PD | Predicate disambiguation | batch_69e3b02ac8688190a7182f1b2151d721 |
completed | April 18, 2026, 4:24 p.m. |
Created at: April 10, 2026, 5:45 a.m.