Triple
T5843621
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Swansea Bay |
E129651
|
entity |
| Predicate | hasNearbyIndustrialArea |
P20649
|
FINISHED |
| Object | Port Talbot industrial area |
—
|
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: Port Talbot industrial area | Statement: [Swansea Bay, hasNearbyIndustrialArea, Port Talbot industrial area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyIndustrialArea Context triple: [Swansea Bay, hasNearbyIndustrialArea, Port Talbot industrial area]
-
A.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
B.
hasNearbyIndustry
chosen
Indicates that an entity is located close to one or more industrial facilities or activities.
-
C.
hasNearbyLandUse
Indicates that one land area is located close to another area characterized by a specific type of land use.
-
D.
hasIndustrialPark
Indicates that a location or entity possesses or contains an industrial park within its area or jurisdiction.
-
E.
hasIndustrialZoning
Indicates that a given area or property is designated for industrial use under zoning regulations.
- 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_69c0084bd31c8190a796bb6284845e83 |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c0334412388190bc594794ec5754f9 |
completed | March 22, 2026, 6:21 p.m. |
Created at: March 22, 2026, 3:55 p.m.