Triple
T6938384
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sector 1 |
E160608
|
entity |
| Predicate | containsPart |
P35
|
FINISHED |
| Object |
Băneasa
Băneasa is a northern district of Bucharest, Romania, known for its residential areas, shopping centers, and proximity to Băneasa Airport and Băneasa Forest.
|
E629485
|
NE FINISHED |
How this triple was built (4 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: Băneasa | Statement: [Sector 1, containsPart, Băneasa]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Băneasa Context triple: [Sector 1, containsPart, Băneasa]
-
A.
Băilești
Băilești is a town in southwestern Romania, in Dolj County, known as a local agricultural and commercial center.
-
B.
Giurgiulești
Giurgiulești is a Moldovan village and river port located at the country’s southern tip, serving as its only direct access point to the Danube and maritime trade routes.
-
C.
Pitești
Pitești is a city in southern Romania, known as an important industrial and transportation hub and the capital of Argeș County.
-
D.
Miercurea Ciuc
Miercurea Ciuc is a town in eastern Transylvania, Romania, known as a cultural center of the Székely Hungarian community and for its cold climate.
-
E.
Bârlad
Bârlad is a town in eastern Romania, historically part of the Moldavia region and known as a local cultural and educational center.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Băneasa Triple: [Sector 1, containsPart, Băneasa]
Generated description
Băneasa is a northern district of Bucharest, Romania, known for its residential areas, shopping centers, and proximity to Băneasa Airport and Băneasa Forest.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Băneasa Target entity description: Băneasa is a northern district of Bucharest, Romania, known for its residential areas, shopping centers, and proximity to Băneasa Airport and Băneasa Forest.
-
A.
Băilești
Băilești is a town in southwestern Romania, in Dolj County, known as a local agricultural and commercial center.
-
B.
Giurgiulești
Giurgiulești is a Moldovan village and river port located at the country’s southern tip, serving as its only direct access point to the Danube and maritime trade routes.
-
C.
Pitești
Pitești is a city in southern Romania, known as an important industrial and transportation hub and the capital of Argeș County.
-
D.
Miercurea Ciuc
Miercurea Ciuc is a town in eastern Transylvania, Romania, known as a cultural center of the Székely Hungarian community and for its cold climate.
-
E.
Bârlad
Bârlad is a town in eastern Romania, historically part of the Moldavia region and known as a local cultural and educational center.
- F. None of above. chosen
Provenance (5 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_69c6884f3db4819080ad65da69386206 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6da62d2f88190968d3fea538a95c9 |
completed | March 27, 2026, 7:28 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c7515509148190b5739cdf8cd7a28a |
completed | March 28, 2026, 3:56 a.m. |
| NEDg | Description generation | batch_69c752c9b3d08190960d3c1aa88a93a7 |
completed | March 28, 2026, 4:02 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c7537ea24c819081bb672d43d4a373 |
completed | March 28, 2026, 4:05 a.m. |
Created at: March 27, 2026, 2:28 p.m.