Triple
T9990270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rummelsburger See |
E196867
|
entity |
| Predicate | hasEnvironmentalHistory |
P91454
|
FINISHED |
| Object | former industrial pollution |
—
|
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: former industrial pollution | Statement: [Rummelsburger See, hasEnvironmentalHistory, former industrial pollution]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEnvironmentalHistory Context triple: [Rummelsburger See, hasEnvironmentalHistory, former industrial pollution]
-
A.
hasNaturalResourceHistory
Indicates that there exists a documented history or record of natural resource–related events, uses, or conditions associated with an entity.
-
B.
hasHistoricalEntity
Indicates a relationship where one entity includes, references, or is associated with another entity that existed or is defined in a past historical context.
-
C.
hasHistoricalLandCover
Indicates that an entity is associated with information about the land cover that existed in a specified area during a past time period.
-
D.
hasHistoricFeatures
Indicates that something possesses characteristics, elements, or attributes of historical significance.
-
E.
historicalLanguageOfEnvironment
Indicates that a language was historically used or prevalent in a given environment or setting, even if it is not the current primary language there.
- F. None of above. chosen
Provenance (4 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_69ca82f1678c819093d06320a05f16a4 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cdc7a0cb6481908d7bd1b43f93bd18 |
completed | April 2, 2026, 1:34 a.m. |
| PD | Predicate disambiguation | batch_69cd1da07db88190945bcdab3ca82e71 |
completed | April 1, 2026, 1:29 p.m. |
| PDg | Predicate description generation | batch_69cd358386f48190833c862b5b8c04b2 |
completed | April 1, 2026, 3:10 p.m. |
Created at: March 30, 2026, 8:50 p.m.