Triple
T2551896
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lady Caroline Lamb |
E56644
|
entity |
| Predicate | portrayedLordByronAs |
P40787
|
FINISHED |
| Object | ruthless seducer in Glenarvon |
—
|
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: ruthless seducer in Glenarvon | Statement: [Lady Caroline Lamb, portrayedLordByronAs, ruthless seducer in Glenarvon]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: portrayedLordByronAs Context triple: [Lady Caroline Lamb, portrayedLordByronAs, ruthless seducer in Glenarvon]
-
A.
portrayedBy
Indicates that one entity serves as the actor or performer who represents or plays the role of another entity in a work or medium.
-
B.
portraysActorAs
Indicates that one entity depicts or represents an actor in a particular role, character, or manner.
-
C.
portrayedByWork
Indicates that a work (such as a film, book, or artwork) depicts, represents, or portrays a particular entity.
-
D.
portraysDonJuanAs
Indicates that a subject represents or depicts Don Juan in a particular manner, role, or characterization.
-
E.
portrayedVia
Indicates that one entity is represented, depicted, or expressed through a particular medium, method, or channel.
- 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_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. |
| PDg | Predicate description generation | batch_69abd5a1cd508190a660b9a3c6b7cbcb |
completed | March 7, 2026, 7:37 a.m. |
Created at: March 6, 2026, 9:48 p.m.