Triple
T23947986
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Xincan languages |
E602964
|
entity |
| Predicate | hasLinguisticResearcher |
P28320
|
FINISHED |
| Object | Lyle Campbell |
—
|
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: Lyle Campbell | Statement: [Xincan languages, hasLinguisticResearcher, Lyle Campbell]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinguisticResearcher Context triple: [Xincan languages, hasLinguisticResearcher, Lyle Campbell]
-
A.
hasLinguist
Indicates that an entity is associated with or possesses a linguist, typically as a member, employee, collaborator, or resource.
-
B.
hasResearcher
chosen
Indicates that an entity is associated with or linked to a specific researcher responsible for work, study, or investigation related to it.
-
C.
hasPrimaryLanguageOfResearch
Indicates that an entity’s main or principal language used for conducting and publishing research is a specified language.
-
D.
hasLinguisticAffiliation
Indicates a relationship where an entity is associated with or belongs to a particular language or linguistic group.
-
E.
hasLinguisticDocumentation
Indicates that there exists recorded linguistic information or documentation about the language or linguistic properties of the subject.
- 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_69e2953e4924819093f1c24c03476b42 |
completed | April 17, 2026, 8:17 p.m. |
| NER | Named-entity recognition | batch_69f1d02fb4fc8190835baf3bcf909d4d |
completed | April 29, 2026, 9:32 a.m. |
| PD | Predicate disambiguation | batch_69f1615518088190a206f54e2fdb14a3 |
completed | April 29, 2026, 1:39 a.m. |
Created at: April 17, 2026, 9:18 p.m.