Triple
T6032145
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deans Industrial Estate |
E134329
|
entity |
| Predicate | hasTypeOfBusinesses |
P68868
|
FINISHED |
| Object | manufacturing |
—
|
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: manufacturing | Statement: [Deans Industrial Estate, hasTypeOfBusinesses, manufacturing]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypeOfBusinesses Context triple: [Deans Industrial Estate, hasTypeOfBusinesses, manufacturing]
-
A.
hasBusinessTypeAlong
Indicates that a business or commercial entity located along a route, corridor, or area is associated with a specific type or category of business activity.
-
B.
eligibleBusinessType
Indicates that a business entity qualifies under specified criteria to be considered an eligible type for a particular program, rule, or context.
-
C.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
D.
hasTypeOfOrganization
Indicates that an entity is classified as belonging to a particular type or category of organization.
-
E.
concernsBusinessType
Indicates that something is related or applicable to a particular type or category of business.
- 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_69c0087515148190a97475d412563865 |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c056b0a8d081909035e2e85e851ca1 |
completed | March 22, 2026, 8:53 p.m. |
| PD | Predicate disambiguation | batch_69c049e9a68c81909da0cfe4779ce9b5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:08 p.m.