Triple
T36666635
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dannenberg (Elbe) |
E905281
|
entity |
| Predicate | hasNearbyNuclearFacility |
P103461
|
FINISHED |
| Object | Gorleben nuclear waste site |
—
|
NE NERFINISHED |
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: Gorleben nuclear waste site | Statement: [Dannenberg (Elbe), hasNearbyNuclearFacility, Gorleben nuclear waste site]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyNuclearFacility Context triple: [Dannenberg (Elbe), hasNearbyNuclearFacility, Gorleben nuclear waste site]
-
A.
hasNuclearPowerPlantNearby
chosen
Indicates that an entity is located close to at least one nuclear power plant.
-
B.
isNuclearSite
Indicates that a location or facility is used for nuclear-related activities, such as power generation, research, weapons development, or radioactive material storage.
-
C.
nuclearReactorLocation
Indicates the place where a nuclear reactor is situated or operates.
-
D.
hasNuclearAccidentAssociation
Indicates a relationship in which an entity is connected or linked to a nuclear accident, such as by involvement, impact, or relevance.
-
E.
hasNuclearReactor
Indicates that an entity possesses, contains, or is equipped with a nuclear reactor.
- 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_69f76e6f10008190aea41746aa1b186e |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a0064f8efa48190956287f548a8057d |
completed | May 10, 2026, 10:59 a.m. |
| PD | Predicate disambiguation | batch_6a006471e75c8190adae99bd75e7411b |
completed | May 10, 2026, 10:56 a.m. |
Created at: May 3, 2026, 4:12 p.m.