Triple
T996525
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cynewulf |
E21506
|
entity |
| Predicate | uncertainDetail |
P9778
|
FINISHED |
| Object | exact dates of birth and death unknown |
—
|
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: exact dates of birth and death unknown | Statement: [Cynewulf, uncertainDetail, exact dates of birth and death unknown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uncertainDetail Context triple: [Cynewulf, uncertainDetail, exact dates of birth and death unknown]
-
A.
uncertainty
Indicates that there is doubt, lack of sureness, or incomplete confidence about a fact, outcome, or state of affairs in the relationship or situation described.
-
B.
hasUncertainty
chosen
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
C.
covered
Indicates that one entity lies over or on top of another entity so as to conceal, protect, or obscure it.
-
D.
discloses
Indicates that one entity reveals, makes known, or provides previously non-public information to another entity or to the public.
-
E.
scopeDetail
Indicates a more specific or refined characterization of the extent, boundaries, or coverage of something within a broader scope.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4df6dcc819084a7c0a50637a2c2 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2af071c819086c374a16307dfe0 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.