Triple
T29800382
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Meg Merrilies |
E756676
|
entity |
| Predicate | playsCrucialRoleIn |
P3512
|
FINISHED |
| Object | plot of Guy Mannering |
—
|
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: plot of Guy Mannering | Statement: [Meg Merrilies, playsCrucialRoleIn, plot of Guy Mannering]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: playsCrucialRoleIn Context triple: [Meg Merrilies, playsCrucialRoleIn, plot of Guy Mannering]
-
A.
playsInRole
Indicates that an entity performs or appears in a specific role within a production, event, or context.
-
B.
playedKeyRoleIn
chosen
Indicates that an entity had a major, influential, or decisive impact on the occurrence, outcome, or success of another entity or event.
-
C.
playedEarlyRoleIn
Indicates that one entity contributed significantly to the initial or formative stages of another entity’s development, success, or emergence.
-
D.
has part in role
Indicates that an entity participates as a component or constituent specifically in a defined role within a larger whole or process.
-
E.
playedRoleIn
Indicates that an entity performed or assumed a specific role or character within a particular event, production, or context.
- 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_69f22454583081908927516cb9938d1d |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_69f6c1265c208190aacd2b551f8f0f82 |
completed | May 3, 2026, 3:29 a.m. |
| PD | Predicate disambiguation | batch_69f6bd2415fc81908c23c311aebce66f |
completed | May 3, 2026, 3:12 a.m. |
Created at: April 29, 2026, 5:18 p.m.