Triple
T8109270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prahova County |
E189305
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Sinaia |
E451203
|
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: Sinaia | Statement: [Prahova County, contains, Sinaia]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sinaia Context triple: [Prahova County, contains, Sinaia]
-
A.
Sinaia
chosen
Sinaia is a Romanian mountain resort town in the Carpathians, famed for Peleș Castle and its historic role as a royal summer residence.
-
B.
Tighina
Tighina is a historic city in present-day Moldova, also known as Bender, which has long held strategic importance on the Dniester River.
-
C.
Baia Mare
Baia Mare is a city in northwestern Romania known for its mining history, surrounding Carpathian landscapes, and role as an important regional cultural and economic center.
-
D.
Tecuci
Tecuci is a town in eastern Romania known as a local transport hub and administrative center in Galați County.
-
E.
Soroca
Soroca is a historic town in northern Moldova known for its well-preserved medieval fortress on the banks of the Dniester River.
- 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_69ca82b9d5848190a24672775d5c5011 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb42fbc57c81908c6be87bbc547085 |
completed | March 31, 2026, 3:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ce0218a3888190a0b224cf93a511de |
completed | April 2, 2026, 5:43 a.m. |
Created at: March 30, 2026, 5:32 p.m.