Triple
T22035187
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | George Roundy |
E544186
|
entity |
| Predicate | hairdressingClientele |
P146352
|
FINISHED |
| Object | wealthy women of Beverly Hills |
—
|
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: wealthy women of Beverly Hills | Statement: [George Roundy, hairdressingClientele, wealthy women of Beverly Hills]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairdressingClientele Context triple: [George Roundy, hairdressingClientele, wealthy women of Beverly Hills]
-
A.
aimOfSalon
Indicates that a particular goal, purpose, or objective is the intended focus or mission of a salon.
-
B.
haircuttingSkill
Indicates the degree to which one entity is capable of effectively cutting another entity’s hair.
-
C.
hairCraftedBy
Indicates that a hairstyle or hair-related work was created or styled by a specific person or agent.
-
D.
typeOfSalon
Indicates the specific category or kind of salon that an entity is classified as.
-
E.
servesHairConcern
Indicates that a product, service, or action addresses or is intended to treat a specific hair-related concern.
- 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_69e11e2f98c8819083e11eab90942a78 |
completed | April 16, 2026, 5:36 p.m. |
| NER | Named-entity recognition | batch_69f127f0594881909caf4fbc3e0a2d50 |
completed | April 28, 2026, 9:34 p.m. |
| PD | Predicate disambiguation | batch_69e6f63b0d048190b241622759aab9de |
completed | April 21, 2026, 3:59 a.m. |
| PDg | Predicate description generation | batch_69e6fad4a540819096cdd5ea08527220 |
completed | April 21, 2026, 4:19 a.m. |
Created at: April 16, 2026, 8:25 p.m.