Triple
T12073073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Raven in the Foregate |
E287472
|
entity |
| Predicate | fictionalPriestVictim |
P50141
|
FINISHED |
| Object | unpopular parish priest in Shrewsbury |
—
|
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: unpopular parish priest in Shrewsbury | Statement: [The Raven in the Foregate, fictionalPriestVictim, unpopular parish priest in Shrewsbury]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalPriestVictim Context triple: [The Raven in the Foregate, fictionalPriestVictim, unpopular parish priest in Shrewsbury]
-
A.
fictionalPrisoner
Indicates that an entity is portrayed as a prisoner within a fictional or narrative context.
-
B.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
C.
fictionalCharacter
chosen
Indicates that one entity is a fictional character that appears within the narrative world of another entity (such as a work, series, or franchise).
-
D.
victimRole
Indicates that one entity participates in an event or situation specifically in the role of the victim or harmed party.
-
E.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
- 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_69d6ab4846e081908ee7bbd66a6d3459 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9100b4ca8819084845ca4c13e34ce |
completed | April 10, 2026, 2:58 p.m. |
| PD | Predicate disambiguation | batch_69d902bda47c8190b94860b31df4a98c |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:48 p.m.