Triple
T15977236
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lyutsifer Safin |
E387479
|
entity |
| Predicate | disfigurement |
P75397
|
FINISHED |
| Object | facial scarring |
—
|
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: facial scarring | Statement: [Lyutsifer Safin, disfigurement, facial scarring]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: disfigurement Context triple: [Lyutsifer Safin, disfigurement, facial scarring]
-
A.
defect
Indicates that an entity has a fault, imperfection, or malfunction that causes it to deviate from an expected standard or proper functioning.
-
B.
dismembered
Indicates that one entity has cut or torn another entity’s body into separate parts, typically removing limbs or sections.
-
C.
distorts
Indicates that one entity alters another in a way that changes, warps, or misrepresents its original form, appearance, or meaning.
-
D.
corrupts
Indicates that one entity causes another entity, system, or process to become morally, functionally, or structurally degraded or impaired.
-
E.
hasDeformation
chosen
Indicates that one entity exhibits or is characterized by a physical or structural deformation associated with another entity or condition.
- 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_69d86da94ccc819083d187f5dc6a123e |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e17d4d08f481909f38b75e3f42d9ab |
completed | April 17, 2026, 12:22 a.m. |
| PD | Predicate disambiguation | batch_69e142d9d8e881909b559a3e3ca21d24 |
completed | April 16, 2026, 8:13 p.m. |
Created at: April 10, 2026, 4:54 a.m.