Triple
T22697305
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lăpuș River |
E561215
|
entity |
| Predicate | hasNameInLanguage |
P15
|
FINISHED |
| Object | Lăpuș |
—
|
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: Lăpuș | Statement: [Lăpuș River, hasNameInLanguage, Lăpuș]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lăpuș Context triple: [Lăpuș River, hasNameInLanguage, Lăpuș]
-
A.
Rucăr
Rucăr is a commune in Argeș County, Romania, known for its scenic Carpathian mountain landscapes and traditional rural character.
-
B.
Zalău
Zalău is a city in northwestern Romania that serves as the capital of Sălaj County in the historical region of Transylvania.
-
C.
Lăpuș River
chosen
The Lăpuș River is a watercourse in northwestern Romania that flows through Maramureș County and passes by the town of Seini before joining the Someș River.
-
D.
Reșița
Reșița is an industrial city in western Romania, historically known as a major center of steel production and engineering in the Banat region.
-
E.
Vlăhița
Vlăhița is a small town in central Romania known for its Székely Hungarian community and its location in the scenic Harghita Mountains.
- 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_69e2454e615481909c177440be559d2c |
completed | April 17, 2026, 2:35 p.m. |
| NER | Named-entity recognition | batch_69f1789f26848190bcc5a99e3ed909e7 |
completed | April 29, 2026, 3:18 a.m. |
Created at: April 17, 2026, 3:14 p.m.