Triple
T18835184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bre-Z |
E460644
|
entity |
| Predicate | haircuttingSkill |
P133096
|
FINISHED |
| Object | professional barber experience |
—
|
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: professional barber experience | Statement: [Bre-Z, haircuttingSkill, professional barber experience]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: haircuttingSkill Context triple: [Bre-Z, haircuttingSkill, professional barber experience]
-
A.
hairCutOffBy
Indicates that one entity’s hair is removed or cut off by another entity.
-
B.
haircutNamedAfter
Indicates that a particular hairstyle is named after a specific person, character, place, or other entity.
-
C.
hairCraftedBy
Indicates that a hairstyle or hair-related work was created or styled by a specific person or agent.
-
D.
cuttingStyle
Indicates the manner or technique in which something is cut or shaped.
-
E.
hairType
Indicates the specific kind or category of hair an entity has, such as its texture, style, or structural type.
- F. None of above. chosen
Provenance (4 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_69d8dcfa11e4819090ab1ef5bdcd2b2e |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5a99d491c81909d8e55ac45621d44 |
completed | April 20, 2026, 4:20 a.m. |
| PD | Predicate disambiguation | batch_69e48d1e7dac81909ea1e758c87773c5 |
completed | April 19, 2026, 8:06 a.m. |
| PDg | Predicate description generation | batch_69e49785fd7081909577e90a55df0a35 |
completed | April 19, 2026, 8:51 a.m. |
Created at: April 10, 2026, 11:56 a.m.