Triple
T25703440
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Baron |
E644523
|
entity |
| Predicate | cuts |
P95254
|
FINISHED |
| Object | Belinda’s lock of hair |
—
|
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: Belinda’s lock of hair | Statement: [the Baron, cuts, Belinda’s lock of hair]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cuts Context triple: [the Baron, cuts, Belinda’s lock of hair]
-
A.
cutDown
Indicates that an agent causes something standing or elevated (such as a tree or structure) to fall or be reduced by cutting.
-
B.
commonCut
Indicates that two or more entities share at least one identical segment or portion that has been cut or divided in the same way.
-
C.
crossCut
Indicates that one entity intersects or passes through another, typically cutting across it from one side to the other.
-
D.
cutOff
Indicates that one entity causes another entity to be disconnected, interrupted, or severed from a source, flow, or continuation.
-
E.
cutBy
chosen
Indicates that one entity is divided, severed, or shaped as a result of another entity performing a cutting action on it.
- 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_69e77e83c8ec8190bf52fcdac4838984 |
completed | April 21, 2026, 1:41 p.m. |
| NER | Named-entity recognition | batch_69f5fc0f911c819083ea7748550df1d0 |
completed | May 2, 2026, 1:28 p.m. |
| PD | Predicate disambiguation | batch_69f4807f8680819098a524158d049c63 |
completed | May 1, 2026, 10:29 a.m. |
Created at: April 21, 2026, 8:59 p.m.