Triple
T6690633
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nalik |
E152615
|
entity |
| Predicate | hasSpeakerNumber |
P1247
|
FINISHED |
| Object | several thousand speakers (approximate) |
—
|
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: several thousand speakers (approximate) | Statement: [Nalik, hasSpeakerNumber, several thousand speakers (approximate)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpeakerNumber Context triple: [Nalik, hasSpeakerNumber, several thousand speakers (approximate)]
-
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
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
C.
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.
-
D.
hasMainSpeaker
Indicates that one entity serves as the primary or principal speaker associated with another entity, such as an event, recording, or presentation.
-
E.
hasApproximateTotalSpeakers
chosen
Indicates that an entity is associated with an estimated or roughly calculated number of total speakers, rather than an exact count.
- 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_69c6880687b08190805278b504d1c92c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6cd0fa5188190a23281cb09d98139 |
completed | March 27, 2026, 6:31 p.m. |
| PD | Predicate disambiguation | batch_69c6ad0d3c1081908dadff7a6a054123 |
completed | March 27, 2026, 4:15 p.m. |
Created at: March 27, 2026, 2:04 p.m.