Triple
T22259807
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Heltau |
E550188
|
entity |
| Predicate | hasNameInRomanian |
P23117
|
FINISHED |
| Object | Cisnădie |
—
|
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: Cisnădie | Statement: [Heltau, hasNameInRomanian, Cisnădie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cisnădie Context triple: [Heltau, hasNameInRomanian, Cisnădie]
-
A.
Cisnădie
chosen
Cisnădie is a small town in central Romania’s Sibiu County, known for its historic fortified church and traditional Transylvanian character.
-
B.
Cernavodă
Cernavodă is a town in southeastern Romania best known for its major Danube–Black Sea Canal port and the nearby Cernavodă Nuclear Power Plant.
-
C.
Comănești
Comănești is a town in Bacău County, Romania, known for its location in the Trotuș Valley and its historical role in the region’s timber and coal industries.
-
D.
Săpânța
Săpânța is a village in northern Romania renowned for its colorful and humorous "Merry Cemetery," a unique open-air museum of painted wooden crosses and epitaphs.
-
E.
Caransebeș
Caransebeș is a historic town in western Romania, situated in the Banat region and known as an important local cultural and transportation hub.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e42adb8819087714772ea606709 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f138c5b54c8190854690ba599639fa |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 16, 2026, 8:39 p.m.