Triple
T36378271
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | River Blyth |
E895968
|
entity |
| Predicate | nearbyIndustrialUse |
P19783
|
FINISHED |
| Object | coal export (historically) |
—
|
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: coal export (historically) | Statement: [River Blyth, nearbyIndustrialUse, coal export (historically)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: nearbyIndustrialUse Context triple: [River Blyth, nearbyIndustrialUse, coal export (historically)]
-
A.
nearbyIndustrialInstallation
Indicates that one entity is located close to an industrial facility or installation.
-
B.
adjacentToIndustrialArea
Indicates that one entity is located directly next to or bordering an industrial area.
-
C.
nearIndustrialComplex
Indicates that one entity is located in close proximity to an industrial complex.
-
D.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
-
E.
hasNearbyLandUse
chosen
Indicates that one land area is located close to another area characterized by a specific type of land use.
- 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_69f76e51d358819092bbc5f119f49476 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69fee335cb08819097e3a0e09d5ebf49 |
completed | May 9, 2026, 7:33 a.m. |
| PD | Predicate disambiguation | batch_69fee2c74fd88190acfc045ab07b7f6b |
completed | May 9, 2026, 7:31 a.m. |
Created at: May 3, 2026, 4:10 p.m.