Triple
T12187244
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | magicJack |
E290363
|
entity |
| Predicate | professionalCategory |
P103653
|
FINISHED |
| Object | professional women's soccer club in the United States |
—
|
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 women's soccer club in the United States | Statement: [magicJack, professionalCategory, professional women's soccer club in the United States]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: professionalCategory Context triple: [magicJack, professionalCategory, professional women's soccer club in the United States]
-
A.
professionalSector
Indicates the industry or field in which an entity conducts its professional or occupational activities.
-
B.
professionalBody
Indicates that an entity is a formal organization that represents, regulates, or supports members of a particular profession.
-
C.
professionalClass
Indicates that an entity belongs to, or is categorized within, a particular professional or occupational class.
-
D.
professionalScope
Indicates the range of activities, responsibilities, or roles that fall within a person’s or organization’s recognized professional duties or expertise.
-
E.
professionalWins
Indicates that one entity has achieved a certain number of victories or successes in a professional context, such as in a career, competition, or formal domain.
- 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_69d6ab64de5881908d56eb7a75c6cc69 |
completed | April 8, 2026, 7:24 p.m. |
| NER | Named-entity recognition | batch_69d91a83012c81908d04bbab5fdcd8c2 |
completed | April 10, 2026, 3:42 p.m. |
| PD | Predicate disambiguation | batch_69d91510a258819090ef8fbdc2d8707b |
completed | April 10, 2026, 3:19 p.m. |
| PDg | Predicate description generation | batch_69d91a7e0fc081909ec9769231e728a4 |
completed | April 10, 2026, 3:42 p.m. |
Created at: April 8, 2026, 9:50 p.m.