Triple
T2534000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Atlantic–Congo languages |
E56225
|
entity |
| Predicate | macroFamilySize |
P40930
|
FINISHED |
| Object | hundreds of languages |
—
|
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: hundreds of languages | Statement: [Atlantic–Congo languages, macroFamilySize, hundreds of languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: macroFamilySize Context triple: [Atlantic–Congo languages, macroFamilySize, hundreds of languages]
-
A.
familySize
Indicates the number of individuals that belong to a given family unit.
-
B.
macroFamilyStatus
Indicates the broad genealogical relationship between languages or language families at the macro-family level.
-
C.
numberOfFamilies
Indicates the total count of distinct family units associated with a given entity or context.
-
D.
macroFamily
Indicates that two or more language families are hypothesized to share a common higher-level genetic origin, forming a larger proposed macro-family grouping.
-
E.
familyType
Indicates the specific familial relationship or category that characterizes how the related entities are connected as family.
- 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_69ab4a49b6508190bc467fbef4bac334 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd64a2194819097c66cbeb37fe859 |
completed | March 7, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69abd0c4a5dc819097812db50443420a |
completed | March 7, 2026, 7:16 a.m. |
| PDg | Predicate description generation | batch_69abd648487881908ce8ca22def77294 |
completed | March 7, 2026, 7:39 a.m. |
Created at: March 6, 2026, 9:47 p.m.