Triple
T2267338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Moscow Central Diameters |
E50176
|
entity |
| Predicate | hasLine |
P35
|
FINISHED |
| Object |
D3
D3 is one of the commuter rail lines of the Moscow Central Diameters urban rail system, connecting Moscow with its surrounding suburbs.
|
E250701
|
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: D3 | Statement: [Moscow Central Diameters, hasLine, D3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: D3 Context triple: [Moscow Central Diameters, hasLine, D3]
-
A.
D
D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
-
B.
D
The D is a New York City Subway service that runs on the IND Sixth Avenue Line in Manhattan and connects Rockefeller Center with other major destinations across the city.
-
C.
D
D is the vehicle registration code used on license plates for the German city of Düsseldorf.
-
D.
D-2
D-2 was a 1993 German-led Spacelab space shuttle mission focused on microgravity and life sciences research in low Earth orbit.
-
E.
The D
"The D" is a popular nickname for Detroit, a major U.S. city known for its automotive industry, musical heritage, and role in American industrial history.
- 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: D3 Triple: [Moscow Central Diameters, hasLine, D3]
Generated description
D3 is one of the commuter rail lines of the Moscow Central Diameters urban rail system, connecting Moscow with its surrounding suburbs.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: D3 Target entity description: D3 is one of the commuter rail lines of the Moscow Central Diameters urban rail system, connecting Moscow with its surrounding suburbs.
-
A.
D
D is a statically typed, compiled systems programming language designed as a modern successor to C and C++, emphasizing high performance, safety features, and programmer productivity.
-
B.
D
The D is a New York City Subway service that runs on the IND Sixth Avenue Line in Manhattan and connects Rockefeller Center with other major destinations across the city.
-
C.
D
D is the vehicle registration code used on license plates for the German city of Düsseldorf.
-
D.
D-2
D-2 was a 1993 German-led Spacelab space shuttle mission focused on microgravity and life sciences research in low Earth orbit.
-
E.
The D
"The D" is a popular nickname for Detroit, a major U.S. city known for its automotive industry, musical heritage, and role in American industrial history.
- 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_69a88b01e0048190ba96431b5f990ba9 |
completed | March 4, 2026, 7:41 p.m. |
| NER | Named-entity recognition | batch_69abc1baa0948190b07ffc347a4f714e |
completed | March 7, 2026, 6:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae71d492a48190be58396831e87ea0 |
completed | March 9, 2026, 7:08 a.m. |
| NEDg | Description generation | batch_69ae72bdc5dc81908f475353999161e4 |
completed | March 9, 2026, 7:11 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae76720e3c8190aeb82dd8779ff715 |
completed | March 9, 2026, 7:27 a.m. |
Created at: March 4, 2026, 7:48 p.m.