Triple
T2010970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prince |
E43685
|
entity |
| Predicate | usedFaceMarking |
P4957
|
FINISHED |
| Object | the word "slave" written on his face during label dispute |
—
|
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: the word "slave" written on his face during label dispute | Statement: [Prince, usedFaceMarking, the word "slave" written on his face during label dispute]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedFaceMarking Context triple: [Prince, usedFaceMarking, the word "slave" written on his face during label dispute]
-
A.
usedOwnFaceAsModelFor
Indicates that an entity created or designed something using their own face as the reference or template.
-
B.
facesChallenge
Indicates that an entity is confronted with a difficulty, obstacle, or demanding situation that must be dealt with or overcome.
-
C.
defacedWith
chosen
Indicates that one entity has been damaged, marred, or vandalized using another entity as the means or material of defacement.
-
D.
usedLabel
Indicates that one entity has applied, assigned, or referenced a particular label to another entity or resource.
-
E.
faceType
Indicates the specific shape or structural category of a face that an entity possesses or is characterized by.
- 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_69a88716e9f08190946313fdc949e3cf |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb8b150a8819096c919465fd91ab5 |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb7a03a1c81909ad50d56667db2d5 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.