Triple
T9440131
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kakhovka Reservoir |
E227621
|
entity |
| Predicate | locatedNearCity |
P3883
|
FINISHED |
| Object | Enerhodar |
E495474
|
NE 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: Enerhodar | Statement: [Kakhovka Reservoir, locatedNearCity, Enerhodar]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Enerhodar Context triple: [Kakhovka Reservoir, locatedNearCity, Enerhodar]
-
A.
Energodar
chosen
Energodar is a Ukrainian city best known for hosting the Zaporizhzhia Nuclear Power Plant, the largest nuclear power station in Europe.
-
B.
Energetica
Energetica is an interactive exhibition at Amsterdam’s NEMO Science Museum that explores the principles and applications of sustainable energy and natural forces.
-
C.
Electryon
Electryon is a king of Mycenae in Greek mythology, known primarily as the grandfather of the hero Heracles.
-
D.
Kenergy
Kenergy is a playful pop-culture term capturing the exuberant, slightly oblivious yet endearing masculine vibe embodied by Ryan Gosling’s portrayal of Ken in the Barbie movie.
-
E.
Stroman
Stroman is a surname most prominently associated with Susan Stroman, the acclaimed American theatre director and choreographer known for her work on Broadway musicals.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca843884488190ad6cbe0153088234 |
completed | March 30, 2026, 2:10 p.m. |
| NER | Named-entity recognition | batch_69cd7ee36f908190826994db91b18466 |
completed | April 1, 2026, 8:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1105909248190b3e02a1aa5f06b11 |
completed | April 4, 2026, 1:21 p.m. |
Created at: March 30, 2026, 7:50 p.m.