Triple
T23696247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sossenheim |
E585453
|
entity |
| Predicate | hasIndustrialProximity |
P112395
|
FINISHED |
| Object | industrial areas along the Main River |
—
|
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: industrial areas along the Main River | Statement: [Sossenheim, hasIndustrialProximity, industrial areas along the Main River]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIndustrialProximity Context triple: [Sossenheim, hasIndustrialProximity, industrial areas along the Main River]
-
A.
hasNearbyIndustry
Indicates that an entity is located close to one or more industrial facilities or activities.
-
B.
connectsToIndustrialArea
Indicates that one entity has a direct link, route, or access connection to an industrial area.
-
C.
hasIndustrialZoneAlong
chosen
Indicates that an industrial zone is located adjacent to or extending along the length of a specified linear feature (such as a road, river, or boundary).
-
D.
hasIndustrialAreaType
Indicates that an entity’s industrial area is classified as a specific type or category of industrial zone.
-
E.
containsIndustrialAreas
Indicates that one entity includes or encompasses industrial areas within its boundaries or scope.
- 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_69e24904bd508190abfcb74855de2918 |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b5c65ab88190be59a8fb731cf030 |
completed | April 29, 2026, 7:39 a.m. |
| PD | Predicate disambiguation | batch_69f155d5265881908e43a9696b6a6d0f |
completed | April 29, 2026, 12:50 a.m. |
Created at: April 17, 2026, 6:52 p.m.