Triple
T13572516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Talbot Road |
E324198
|
entity |
| Predicate | hasBusinesses |
P110112
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Talbot Road, hasBusinesses, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasBusinesses Context triple: [Talbot Road, hasBusinesses, yes]
-
A.
hasBusiness
Indicates that one entity owns, operates, or is formally associated with a business entity.
-
B.
hasTypeOfBusinesses
Indicates that an entity is associated with or contains specific categories or kinds of businesses.
-
C.
hasBusinessNode
Indicates that an entity is associated with, linked to, or represented by a specific business-related node within a business structure or network.
-
D.
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.
-
E.
hasBusinessCenter
Indicates that an entity includes, contains, or is equipped with a business center facility.
- 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_69d80769100c819099111274614f5ed2 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbb0106cb48190b20eb9bda131a68a |
completed | April 12, 2026, 2:45 p.m. |
| PD | Predicate disambiguation | batch_69dbae161a0481909f9d3f40ca4e0ac5 |
completed | April 12, 2026, 2:37 p.m. |
| PDg | Predicate description generation | batch_69dbaf7fefa881908471f1400f813ccc |
completed | April 12, 2026, 2:43 p.m. |
Created at: April 9, 2026, 9:48 p.m.