Triple
T24327034
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Königshütte, Silesia, German Empire |
E613127
|
entity |
| Predicate | adjacentIndustry |
P20649
|
FINISHED |
| Object | coal mines |
—
|
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 mines | Statement: [Königshütte, Silesia, German Empire, adjacentIndustry, coal mines]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentIndustry Context triple: [Königshütte, Silesia, German Empire, adjacentIndustry, coal mines]
-
A.
hasNearbyIndustry
chosen
Indicates that an entity is located close to one or more industrial facilities or activities.
-
B.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
C.
industryActivities
Indicates the types of economic or business activities in which an industry or sector is engaged.
-
D.
associatedIndustrySite
Indicates that one entity is linked or related to another entity that represents an industry-specific website or online resource.
-
E.
hasRelativeInSameIndustry
Indicates that one entity has a relative who works in the same industry as the 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_69e2d7db6d5c819091194918157a7c1f |
completed | April 18, 2026, 1:01 a.m. |
| NER | Named-entity recognition | batch_69f292edb6f481909f0a6a7592fd7d6a |
completed | April 29, 2026, 11:23 p.m. |
| PD | Predicate disambiguation | batch_69f287ad30048190b3ad3613486f277f |
completed | April 29, 2026, 10:35 p.m. |
Created at: April 18, 2026, 1:54 a.m.