Triple
T30684200
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Clifford |
E781138
|
entity |
| Predicate | hasLinguisticOriginPeriod |
P193311
|
FINISHED |
| Object | early medieval England |
—
|
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: early medieval England | Statement: [Clifford, hasLinguisticOriginPeriod, early medieval England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLinguisticOriginPeriod Context triple: [Clifford, hasLinguisticOriginPeriod, early medieval England]
-
A.
hasLanguagePeriod
Indicates a relationship where a language is associated with a specific historical or temporal period during which it was used or recognized.
-
B.
hasLinguisticHeritage
Indicates that one entity possesses or is associated with the linguistic background, tradition, or ancestry of another entity.
-
C.
hasLinguisticLegacy
Indicates that one entity has left a lasting influence or enduring impact on the language, linguistic practices, or linguistic development associated with another entity.
-
D.
vernacularLanguagePeriod
Indicates the time span during which a particular vernacular (locally spoken) language was in use or predominant in a given context.
-
E.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
- 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_69f224a92f54819095499b4d32bd5134 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd4129a8848190a5002150278ac689 |
completed | May 8, 2026, 1:49 a.m. |
| PD | Predicate disambiguation | batch_69fd3e0515ec8190937c7af71ebc3875 |
completed | May 8, 2026, 1:36 a.m. |
| PDg | Predicate description generation | batch_69fd4128ed908190837ec9936774a1cf |
completed | May 8, 2026, 1:49 a.m. |
Created at: April 29, 2026, 8:33 p.m.