Triple
T10114063
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Burkitt Medal for Biblical Studies |
E218311
|
entity |
| Predicate | languageOfField |
P92276
|
FINISHED |
| Object | primarily English |
—
|
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: primarily English | Statement: [Burkitt Medal for Biblical Studies, languageOfField, primarily English]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: languageOfField Context triple: [Burkitt Medal for Biblical Studies, languageOfField, primarily English]
-
A.
languageOfRecords
Indicates the language in which the records are written or maintained.
-
B.
linguisticField
Indicates that something pertains to or is associated with a particular area or subdiscipline within linguistics.
-
C.
languageForm
Indicates the specific linguistic form or expression in which something is conveyed or represented.
-
D.
languageOfVariant
Indicates that one entity is the language in which a particular variant or version of another entity is expressed.
-
E.
languageLabel
Indicates the human-readable name or label of a language associated with an entity or resource.
- 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_69ca83da93fc8190b54e44bc2b34857c |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cdd15ffcd48190825800611aab2aab |
completed | April 2, 2026, 2:16 a.m. |
| PD | Predicate disambiguation | batch_69cd4b9ed7e48190aa132ef8a69b49f9 |
completed | April 1, 2026, 4:45 p.m. |
| PDg | Predicate description generation | batch_69cd4f8f869c8190a82ad040993e0244 |
completed | April 1, 2026, 5:02 p.m. |
Created at: March 30, 2026, 9:04 p.m.