Triple
T2930783
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince Edward |
E78954
|
entity |
| Predicate | mistakenFor |
P2289
|
FINISHED |
| Object | pauper |
—
|
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: pauper | Statement: [Prince Edward, mistakenFor, pauper]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mistakenFor Context triple: [Prince Edward, mistakenFor, pauper]
-
A.
misinterpretedBy
Indicates that something (such as a statement, action, or signal) is understood incorrectly or in a way not intended by a particular entity.
-
B.
misrepresentedAs
Indicates that one entity is falsely or inaccurately presented, portrayed, or described as another entity or in another way.
-
C.
wronglyAccusedBy
Indicates that one entity has falsely or unjustly accused another entity of wrongdoing.
-
D.
tricked
Indicates that one entity intentionally deceived another into believing something false or acting under a false impression.
-
E.
oftenConfusedWith
chosen
Indicates that one entity is frequently mistaken for or thought to be another due to similarity or ambiguity.
- 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_69ad8b0d40b481908bc2a5fa2e73c3fb |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad980191388190ac2455a7d9867be3 |
completed | March 8, 2026, 3:38 p.m. |
| PD | Predicate disambiguation | batch_69ad9606e8348190bb19df33a2709674 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:55 p.m.