Triple
T9768450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gheorghe |
E237057
|
entity |
| Predicate | hasFeminineForm |
P1613
|
FINISHED |
| Object | Gheorghina |
E790765
|
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: Gheorghina | Statement: [Gheorghe, hasFeminineForm, Gheorghina]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Gheorghina Context triple: [Gheorghe, hasFeminineForm, Gheorghina]
-
A.
Nicoleta
chosen
Nicoleta is a Romanian feminine given name commonly used in Eastern Europe.
-
B.
Colentina
Colentina is a residential neighborhood in northeastern Bucharest, Romania, known for its dense housing, commercial areas, and location along the Colentina River.
-
C.
Ungheni
Ungheni is a town situated on the Prut River in western Moldova, known as an important border crossing and transport hub between Moldova and Romania.
-
D.
Giurgiu
Giurgiu is a city in southern Romania on the Danube River, serving as an important border crossing and transport link with the Bulgarian city of Ruse.
-
E.
Gheorgheni
Gheorgheni is a town in Harghita County, Romania, known for its Székely Hungarian community and its location in the Eastern Carpathians.
- 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_69ca84d831b8819090322686b47887ce |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cda0a2da648190836916a45d2998d7 |
completed | April 1, 2026, 10:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1bd05f2588190ab413d26342aa70f |
completed | April 5, 2026, 1:38 a.m. |
Created at: March 30, 2026, 8:25 p.m.