Triple
T1094187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Varhadi |
E24233
|
entity |
| Predicate | hasSpeakerType |
P23805
|
FINISHED |
| Object | primarily rural 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: primarily rural speakers | Statement: [Varhadi, hasSpeakerType, primarily rural speakers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeakerType Context triple: [Varhadi, hasSpeakerType, primarily rural speakers]
-
A.
hasSpeakersIn
Indicates that an entity (such as an event, conference, or session) includes or is associated with speakers located in or belonging to a specified place or group.
-
B.
hasMainSpeaker
Indicates that one entity serves as the primary or principal speaker associated with another entity, such as an event, recording, or presentation.
-
C.
hasSpeech
Indicates that an entity produces, delivers, or is associated with a spoken utterance or verbal expression.
-
D.
hasMicrophones
Indicates that one entity possesses, includes, or is equipped with one or more microphones.
-
E.
hasSound
Indicates that an entity produces, emits, or is associated with a particular sound.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99d1e8c81909cf1178d68d38885 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
| PDg | Predicate description generation | batch_69a4b80f0fb08190a19a50e38ae8f16c |
completed | March 1, 2026, 10:05 p.m. |
Created at: March 1, 2026, 7:42 p.m.