Triple
T12884136
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raphaël de Valentin |
E308180
|
entity |
| Predicate | curseOfAssociatedObject |
P7531
|
FINISHED |
| Object | shortens owner’s life |
—
|
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: shortens owner’s life | Statement: [Raphaël de Valentin, curseOfAssociatedObject, shortens owner’s life]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: curseOfAssociatedObject Context triple: [Raphaël de Valentin, curseOfAssociatedObject, shortens owner’s life]
-
A.
associatedCurse
chosen
Indicates that one entity is linked to, affected by, or bears responsibility for a particular curse related to another entity.
-
B.
associatedDam
Indicates a relationship where one entity is linked or connected to a specific dam, typically as its related or corresponding dam structure.
-
C.
associatedWithAssociation
Indicates a relationship where an entity is linked or connected to a particular association or organization.
-
D.
associatedFault
Indicates a relationship where a given entity is linked to, or occurs in connection with, a specific fault or error condition.
-
E.
associatedDemon
Indicates that there exists a relationship in which one entity is linked or connected to a particular demon.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97c7f91d08190aac2f6419d3ba992 |
completed | April 10, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69d96fa55b888190ab1612e93c41aec4 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:39 p.m.