Triple
T23997971
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Terri Jones |
E594158
|
entity |
| Predicate | hairSpecialty |
P154562
|
FINISHED |
| Object | women's hairstyles |
—
|
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: women's hairstyles | Statement: [Terri Jones, hairSpecialty, women's hairstyles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hairSpecialty Context triple: [Terri Jones, hairSpecialty, women's hairstyles]
-
A.
hairDetail
Indicates a relationship that specifies particular characteristics or attributes of an entity’s hair, such as style, color, length, or texture.
-
B.
hairType
Indicates the specific kind or category of hair an entity has, such as its texture, style, or structural type.
-
C.
servesHairConcern
Indicates that a product, service, or action addresses or is intended to treat a specific hair-related concern.
-
D.
hairCraftedBy
Indicates that a hairstyle or hair-related work was created or styled by a specific person or agent.
-
E.
hairdressingClientele
Indicates that one entity serves as the customer or client receiving hairdressing services from another entity.
- 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_69e288b9ecf08190b8c94a278f5674fe |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f1d39066f8819096d13bfdd0a047fc |
completed | April 29, 2026, 9:46 a.m. |
| PD | Predicate disambiguation | batch_69f1615994c48190a5de95d3f7e5cd0a |
completed | April 29, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f16e35944c8190b57cfa31f1e9da1b |
completed | April 29, 2026, 2:34 a.m. |
Created at: April 17, 2026, 9:38 p.m.