Triple
T778138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Steinbrenner family |
E16434
|
entity |
| Predicate | businessOrigin |
P19812
|
FINISHED |
| Object | Great Lakes shipping business |
—
|
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: Great Lakes shipping business | Statement: [Steinbrenner family, businessOrigin, Great Lakes shipping business]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessOrigin Context triple: [Steinbrenner family, businessOrigin, Great Lakes shipping business]
-
A.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
-
B.
businessVenture
Indicates a relationship where entities jointly engage in, operate, or are involved with a commercial or entrepreneurial undertaking.
-
C.
businessFunction
Indicates the specific role, activity, or operational function that an entity performs within a business context.
-
D.
business
Indicates that an entity is engaged in commercial or professional activities, such as providing goods or services for profit.
-
E.
commercialIntroduction
Indicates that one entity introduces or connects another entity to a commercial opportunity, partner, product, or service for business purposes.
- 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a90365648190ace53b0f0e87aa68 |
completed | March 1, 2026, 9 p.m. |
| PD | Predicate disambiguation | batch_69a4a50bd23081908908235b8ec9201e |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a8f09d108190b8c83a6169d65c0c |
completed | March 1, 2026, 9 p.m. |
Created at: March 1, 2026, 7:37 p.m.