Triple
T34344344
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Butkus Award |
E881387
|
entity |
| Predicate | hasProfessionalDivision |
P71519
|
FINISHED |
| Object | Professional Butkus Award |
E881387
|
NE 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 Butkus Award | Statement: [Butkus Award, hasProfessionalDivision, Professional Butkus Award]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProfessionalDivision Context triple: [Butkus Award, hasProfessionalDivision, Professional Butkus Award]
-
A.
hasProfessionalSection
chosen
Indicates that an entity includes or is associated with a designated professional section, division, or category within its structure or content.
-
B.
hasProfessionalComponent
Indicates that something includes, involves, or is associated with a professional (work- or career-related) element or aspect.
-
C.
hasDivisionRole
Indicates that an entity holds a specific role or position within a particular division of an organization.
-
D.
hasProfessionalGroup
Indicates that an entity belongs to, is associated with, or is categorized under a particular professional group or category.
-
E.
hasBusinessDivision
Indicates that an organization includes or is composed of a specific business division as a subordinate unit.
- F. None of above.
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_69f349bc55e881908c8e338ef76b0043 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a0301c45274819083b0dd9d335f7ee0 |
completed | May 12, 2026, 10:32 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a36f9e2ec88819092146581f26c304b |
completed | June 20, 2026, 8:36 p.m. |
| PD | Predicate disambiguation | batch_6a03015c272481908a7bfe81befb1764 |
completed | May 12, 2026, 10:30 a.m. |
Created at: May 1, 2026, 1:58 a.m.