Triple
T28647263
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Robert Cain |
E725094
|
entity |
| Predicate | businessFoundedIn |
P168632
|
FINISHED |
| Object | 19th century |
—
|
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: 19th century | Statement: [Robert Cain, businessFoundedIn, 19th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: businessFoundedIn Context triple: [Robert Cain, businessFoundedIn, 19th century]
-
A.
foundedBusinessIn
Indicates that an entity established or started a business in a particular location or jurisdiction.
-
B.
headquartersFoundedCompanyIn
Indicates that a headquarters entity established or founded a particular company.
-
C.
coFoundedIn
Indicates that two or more entities jointly founded something (such as an organization or company) in a specific place or at a specific time.
-
D.
foundedBusinessInLocation
Indicates that an entity established or created a business in a specified geographic location.
-
E.
notableCompanyFoundedIn
Indicates that a company is recognized as notable and was founded in the specified location or time period.
- 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_69f01d8423888190bd2f4e52605bf261 |
completed | April 28, 2026, 2:37 a.m. |
| NER | Named-entity recognition | batch_69f67595fa7c8190b6e9f7a8c700dd97 |
completed | May 2, 2026, 10:07 p.m. |
| PD | Predicate disambiguation | batch_69f673c4abec8190bc2379e66f4af0a9 |
completed | May 2, 2026, 9:59 p.m. |
| PDg | Predicate description generation | batch_69f674df80b08190adb7f7531083bbb1 |
completed | May 2, 2026, 10:04 p.m. |
Created at: April 28, 2026, 4:49 a.m.