Triple
T1111735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gawain Poet |
E11009
|
entity |
| Predicate | uncertainFact |
P9983
|
FINISHED |
| Object | real personal name 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: real personal name unknown | Statement: [The Gawain Poet, uncertainFact, real personal name unknown]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: uncertainFact Context triple: [The Gawain Poet, uncertainFact, real personal name unknown]
-
A.
uncertainty
chosen
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
Indicates that the relationship or value is associated with some level or type of uncertainty rather than being fully definite or precise.
-
C.
fact
Indicates that something is objectively true or has actually occurred, independent of opinion or belief.
-
D.
factFinding
Indicates a process of gathering and verifying information or evidence to determine the truth about a situation or claim.
-
E.
factPattern
Indicates that a specific configuration of facts or circumstances holds in a situation, typically used as the basis for applying rules, reasoning, or legal/logic inferences.
- 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_69a493252a648190ac48f8742474a5e8 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a4bbd92a8c8190a16e55f3f739010f |
completed | March 1, 2026, 10:21 p.m. |
| PD | Predicate disambiguation | batch_69a4bb42990c819080db96478fd4977e |
completed | March 1, 2026, 10:18 p.m. |
Created at: March 1, 2026, 7:43 p.m.