Triple
T30200589
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Disappearance of Lady Frances Carfax |
E767771
|
entity |
| Predicate | fictionalVictim |
P138180
|
FINISHED |
| Object | Lady Frances Carfax |
—
|
NE NERFINISHED |
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: Lady Frances Carfax | Statement: [The Disappearance of Lady Frances Carfax, fictionalVictim, Lady Frances Carfax]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fictionalVictim Context triple: [The Disappearance of Lady Frances Carfax, fictionalVictim, Lady Frances Carfax]
-
A.
fictionalAuthorVictim
Indicates that one entity is the author of a fictional work in which the other entity appears as a victim.
-
B.
victimCharacter
chosen
Indicates that one entity is the victim or target of harm, wrongdoing, or an adverse action carried out by another entity.
-
C.
coVictim
Indicates that two or more entities are victims in the same harmful event or incident.
-
D.
portraysAsVictim
Indicates that one entity represents or depicts another entity as a victim in a given context or narrative.
-
E.
fictionalPrisoner
Indicates that an entity is portrayed as a prisoner within a fictional or narrative 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_69f2247db1108190835c0727c97637c3 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: April 29, 2026, 7:30 p.m.