Triple
T30893549
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gütersloh district |
E786963
|
entity |
| Predicate | majorCompanyLocated |
P117996
|
FINISHED |
| Object | Bertelsmann |
—
|
NE NERFINISHED |
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: Bertelsmann | Statement: [Gütersloh district, majorCompanyLocated, Bertelsmann]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: majorCompanyLocated Context triple: [Gütersloh district, majorCompanyLocated, Bertelsmann]
-
A.
majorCompanyLocatedIn
chosen
Indicates that a major company has its primary presence or headquarters in a specified location.
-
B.
majorCompanyHeadquartered
Indicates that a company is a primary or significant corporate entity whose main headquarters is located in a specified place.
-
C.
listedCompaniesLocation
Indicates the geographic location associated with companies that are publicly listed.
-
D.
usedByCompanyHeadquarteredIn
Indicates that something (such as a product, service, or technology) is utilized by a company whose main headquarters is located in a specified place.
-
E.
employerHeadquarters
Indicates the location where an employer’s main corporate offices or central administrative operations are based.
- F. None of above.
Provenance (3 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_69f224bbfa7c81908448e0c261c523e3 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69fe6b7c785c8190aaab06019f571434 |
completed | May 8, 2026, 11:02 p.m. |
| PD | Predicate disambiguation | batch_69fe68edef20819081c77f9607b944dd |
completed | May 8, 2026, 10:51 p.m. |
Created at: April 29, 2026, 8:49 p.m.