Triple
T32482612
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Reggie Nalder |
E830149
|
entity |
| Predicate | faceCharacteristic |
P167065
|
FINISHED |
| Object | severely scarred facial features |
—
|
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: severely scarred facial features | Statement: [Reggie Nalder, faceCharacteristic, severely scarred facial features]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: faceCharacteristic Context triple: [Reggie Nalder, faceCharacteristic, severely scarred facial features]
-
A.
facesChallenge
Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
-
B.
faceResemblance
Indicates that one entity’s facial appearance is similar to or resembles that of another entity.
-
C.
hasFacialProfile
chosen
Indicates that an entity possesses a specific facial profile or configuration of facial features.
-
D.
faceValueType
Indicates the type or category of a financial instrument’s face (nominal) value, such as how that value is defined or represented.
-
E.
hasFace
Indicates that one entity possesses, displays, or is characterized by a face.
- 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_69f3491ff3b48190b50a7fa00bb05b1f |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c396f8b881909a940437d9c817ea |
completed | May 3, 2026, 3:40 a.m. |
| PD | Predicate disambiguation | batch_69f6bd25bed08190befcabd3a41ffadf |
completed | May 3, 2026, 3:12 a.m. |
Created at: May 1, 2026, 12:58 a.m.