Triple
T31749889
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bryneich |
E810385
|
entity |
| Predicate | hasHistoricalLanguageContact |
P29982
|
FINISHED |
| Object | Old English |
—
|
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: Old English | Statement: [Bryneich, hasHistoricalLanguageContact, Old English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalLanguageContact Context triple: [Bryneich, hasHistoricalLanguageContact, Old English]
-
A.
historicalLanguageContact
chosen
Indicates that two language communities have been in contact in the past in a way that allowed linguistic influence or exchange between them.
-
B.
hasMajorityLanguageHistorically
Indicates that a particular language has historically been the predominant or majority language within a given entity or region.
-
C.
historicalLanguageOfBearers
Indicates that the specified language is historically spoken or used by the bearers of a given name, title, or designation.
-
D.
hasLinguisticHeritage
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
-
E.
hasContactWithLanguage
Indicates that an entity has some form of interaction, exposure, or engagement with a particular language.
- 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_69f348e233cc819083b6695f70cd75d8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69fe38be079c8190a240191ac0e73e3a |
completed | May 8, 2026, 7:25 p.m. |
| PD | Predicate disambiguation | batch_69fe350344508190930de2218156ca02 |
completed | May 8, 2026, 7:09 p.m. |
Created at: April 30, 2026, 11:27 p.m.