Triple
T30924549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kwoth |
E787820
|
entity |
| Predicate | inNuerLanguage |
P170306
|
FINISHED |
| Object | Kwoth nhial |
—
|
NE NERFINISHED |
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: Kwoth nhial | Statement: [Kwoth, inNuerLanguage, Kwoth nhial]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: inNuerLanguage Context triple: [Kwoth, inNuerLanguage, Kwoth nhial]
-
A.
hasInuktitutMeaning
Indicates that one entity serves as the Inuktitut-language meaning or translation of another entity.
-
B.
NFD
Indicates that one entity has been declared or recognized as not fit for duty (NFD) in relation to another entity or context.
-
C.
usesKunya
Indicates that one entity refers to or identifies another entity by a kunya (a teknonymic nickname, typically based on "father/mother of" someone).
-
D.
usesLogogramsFrom
Indicates that one writing system or notation incorporates or employs logographic characters originating from another system.
-
E.
nameInManchuScriptOf
Indicates that one entity is the representation of another entity’s name written in Manchu script.
- 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_69f224bfaca88190b9d0dfcc86297fe9 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f692b82df881909350359a39daa9ff |
completed | May 3, 2026, 12:11 a.m. |
| PD | Predicate disambiguation | batch_69f68b7ec098819080480998038de940 |
completed | May 2, 2026, 11:40 p.m. |
| PDg | Predicate description generation | batch_69f68c517f308190873c1c7e05a0c6d0 |
completed | May 2, 2026, 11:44 p.m. |
Created at: April 29, 2026, 8:51 p.m.