Triple
T2551894
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Caroline Lamb |
E56644
|
entity |
| Predicate | describedLordByronAs |
P976
|
FINISHED |
| Object | mad, bad, and dangerous to know |
—
|
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: mad, bad, and dangerous to know | Statement: [Lady Caroline Lamb, describedLordByronAs, mad, bad, and dangerous to know]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: describedLordByronAs Context triple: [Lady Caroline Lamb, describedLordByronAs, mad, bad, and dangerous to know]
-
A.
describedByAuthorAs
chosen
Indicates that one entity is characterized, labeled, or portrayed in a particular way by an author.
-
B.
isFrequentlyDescribedAs
Indicates that something is often characterized or referred to using a particular description or set of attributes.
-
C.
poet
Indicates that an entity creates poetry or is recognized for engaging in the activity of writing poems.
-
D.
laterDescribedAs
Indicates that an entity is referred to or characterized by a particular description or label at a later time.
-
E.
villainDescription
Indicates that one entity provides a description or characterization of a villainous role or antagonist associated with another entity.
- 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_69ab4a4bfec081908039988ec4c86e28 |
completed | March 6, 2026, 9:42 p.m. |
| NER | Named-entity recognition | batch_69abd5a33234819082ad49fa6594b6be |
completed | March 7, 2026, 7:37 a.m. |
| PD | Predicate disambiguation | batch_69abd0c8b6f08190a68645db3e8b779a |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:48 p.m.