Triple
T33668029
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moreton |
E862542
|
entity |
| Predicate | hasSpellingOrigin |
P195782
|
FINISHED |
| Object | 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: medieval England | Statement: [Moreton, hasSpellingOrigin, medieval England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSpellingOrigin Context triple: [Moreton, hasSpellingOrigin, medieval England]
-
A.
hasMisspellingOrigin
Indicates that one entity is the source or cause of another entity’s misspelling.
-
B.
hasLanguageOfOrigin
Indicates that one entity has its origin or source in the language specified by another entity.
-
C.
hasDialectalOriginOf
Indicates that something originates from or is derived from a particular dialect.
-
D.
originalSpelling
Indicates that one entity provides the initial or historically first-used spelling form of another entity’s name or term.
-
E.
hasAcronymOrigin
Indicates that an acronym is derived from or originates from a specific longer expression or name.
- 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_69f34984c4008190bb82f33a7819da64 |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69fde5d7d9548190880a9d95b8f0f66b |
completed | May 8, 2026, 1:32 p.m. |
| PD | Predicate disambiguation | batch_69fde4e1bf9c81909754545275eccc03 |
completed | May 8, 2026, 1:28 p.m. |
| PDg | Predicate description generation | batch_69fde5d677b88190bc904e6df8617c18 |
completed | May 8, 2026, 1:32 p.m. |
Created at: May 1, 2026, 1:42 a.m.