Triple
T9726035
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miya |
E235613
|
entity |
| Predicate | hasSpeakerNumberRange |
P36744
|
FINISHED |
| Object | "a few thousand" |
—
|
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: "a few thousand" | Statement: [Miya, hasSpeakerNumberRange, "a few thousand"]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeakerNumberRange Context triple: [Miya, hasSpeakerNumberRange, "a few thousand"]
-
A.
hasSpeakerType
Indicates that an entity functions in a particular role or category as a speaker (e.g., narrator, character, announcer) within a given context.
-
B.
haveSpeakerPopulation
chosen
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
C.
speakerNumber
Indicates the number of distinct speakers involved in a given speech, dialogue, or conversational instance.
-
D.
numberOfSpeakersDate
Indicates the number of speakers associated with an entity as measured or recorded on a specific date.
-
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_69ca84d0fad481909cdd45aa77416c48 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9e798c348190885b79d7dffc9d8d |
completed | April 1, 2026, 10:38 p.m. |
| PD | Predicate disambiguation | batch_69cd03c6ffc88190a5e9569e19122ad5 |
completed | April 1, 2026, 11:38 a.m. |
Created at: March 30, 2026, 8:21 p.m.