Triple
T2403393
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gumuz languages |
E50219
|
entity |
| Predicate | haveApproximateNumberOfSpeakers |
P1247
|
FINISHED |
| Object | 200000 |
—
|
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: 200000 | Statement: [Gumuz languages, haveApproximateNumberOfSpeakers, 200000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haveApproximateNumberOfSpeakers Context triple: [Gumuz languages, haveApproximateNumberOfSpeakers, 200000]
-
A.
hasApproximateTotalSpeakers
chosen
Indicates that an entity is associated with an estimated or roughly calculated number of total speakers, rather than an exact count.
-
B.
haveSpeakerPopulation
Indicates that an entity has a specified number or population size of people who speak a particular language.
-
C.
hasApproximateNativeSpeakers
Indicates that an entity is associated with an estimated or approximate number of people who speak it as their native language.
-
D.
hasApproximateNumberOfLanguages
Indicates that an entity is associated with a quantity representing an estimated or non-exact count of languages.
-
E.
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.
- 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_69a88b0339a88190a1207333cd271cc9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abceab9ce881909ae0a2f34515c11e |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5a530e8819094105aa92dfaf6b3 |
completed | March 7, 2026, 6:28 a.m. |
Created at: March 4, 2026, 7:58 p.m.