Triple
T11593287
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vâlcea County |
E274937
|
entity |
| Predicate | hasTown |
P847
|
FINISHED |
| Object | Călimănești |
E464412
|
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: Călimănești | Statement: [Vâlcea County, hasTown, Călimănești]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Călimănești Context triple: [Vâlcea County, hasTown, Călimănești]
-
A.
Călimănești
chosen
Călimănești is a Romanian spa town in Vâlcea County, known for its thermal springs and historic religious sites in the Olt River valley.
-
B.
Giulești
Giulești is a residential neighborhood in western Bucharest, Romania, known for its working-class character and association with the Rapid București football club.
-
C.
Crângași
Crângași is a residential neighborhood in western Bucharest, Romania, known for its large park and lakeside recreational areas along Lacul Morii.
-
D.
Ploești
Ploești is a major Romanian city historically known for its oil industry and strategic importance, particularly during World War II.
-
E.
Bălcești
Bălcești is a small town in Vâlcea County, Romania, situated in the historical region of Oltenia.
- 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_69d6aae6b14c81908dc5a74bad7591f9 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8946594348190935106132fd18028 |
completed | April 10, 2026, 6:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e7146fdd8c8190a54f3290e155e900 |
completed | April 21, 2026, 6:08 a.m. |
Created at: April 8, 2026, 9:38 p.m.