Triple
T6484336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Tees |
E146470
|
entity |
| Predicate | notableIndustryAlong |
P50235
|
FINISHED |
| Object | steel |
—
|
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: steel | Statement: [River Tees, notableIndustryAlong, steel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableIndustryAlong Context triple: [River Tees, notableIndustryAlong, steel]
-
A.
notableIndustry
Indicates that an entity is significantly recognized or prominent within a specified industry or sector.
-
B.
notableSector
chosen
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
C.
notableBusinessType
Indicates that an entity is notably associated with, characterized by, or best known for a particular type of business.
-
D.
notableOrganizationWithin
Indicates that one organization is a prominent or significant entity operating within the scope, structure, or domain of another organization.
-
E.
notableCommercial
Indicates that an entity is particularly well-known or significant in a commercial context, such as advertising, marketing, or business promotion.
- 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_69c0090158c08190af0df9a2348d2d52 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c06a6de31c81909dd99d105f5bb4c2 |
completed | March 22, 2026, 10:17 p.m. |
| PD | Predicate disambiguation | batch_69c0673f6d48819080e10c85155c7195 |
completed | March 22, 2026, 10:03 p.m. |
Created at: March 22, 2026, 4:52 p.m.