Triple
T8857855
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Leeds Beckett University |
E210803
|
entity |
| Predicate | hasStrongLinksWith |
P43975
|
FINISHED |
| Object | industry |
—
|
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: industry | Statement: [Leeds Beckett University, hasStrongLinksWith, industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasStrongLinksWith Context triple: [Leeds Beckett University, hasStrongLinksWith, industry]
-
A.
hasCoupling
Indicates that two entities are linked or joined together in a way that allows them to interact, transfer, or coordinate motion, energy, or information.
-
B.
hasNotableConnectionTo
chosen
Indicates a significant or noteworthy relationship, association, or link exists between two entities.
-
C.
hasCommunityLink
Indicates that there exists an established connection or association between an entity and a community.
-
D.
hasArc
Indicates that there is a directed connection or edge from one entity to another, often representing a link in a graph or network.
-
E.
hasNumberOfLiaisons
Indicates the quantity of liaison roles, connections, or intermediary relationships associated with a given entity.
- 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_69ca838bbddc8190ab546d737e5d350f |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc60e3b62c8190bf779e7e1db767f6 |
completed | April 1, 2026, 12:03 a.m. |
| PD | Predicate disambiguation | batch_69cc5c279ea481908c71756f694b66bf |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:50 p.m.