Triple
T766404
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pichi language |
E16184
|
entity |
| Predicate | substrateLanguage |
P11299
|
FINISHED |
| Object | Kru 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: Kru languages | Statement: [Pichi language, substrateLanguage, Kru languages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: substrateLanguage Context triple: [Pichi language, substrateLanguage, Kru languages]
-
A.
hasSubstrateLanguage
chosen
Indicates a relationship where one language serves as the underlying substrate that has influenced or shaped another language.
-
B.
languageOfOperation
Indicates the language in which an entity (such as a system, service, or process) primarily operates or functions.
-
C.
languageFeature
Indicates that one entity is a characteristic, property, or capability of a language associated with the other entity.
-
D.
substratePreference
Indicates a relationship where an entity tends to occur on, grow in, or utilize a particular physical material or medium as its preferred substrate.
-
E.
scriptVariantLanguage
Indicates that a language is a variant distinguished by its writing system or script from another, related language form.
- 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_69a493684ee48190bd43b7c78da4aec8 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a765ba688190ab328bb159583077 |
completed | March 1, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69a4a5074c788190a74fc20ad24e2d26 |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.