Triple
T2823843
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cutty Sark DLR station |
E54872
|
entity |
| Predicate | railCode |
P18202
|
FINISHED |
| Object |
CUT
CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
|
E301127
|
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: CUT | Statement: [Cutty Sark DLR station, railCode, CUT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: CUT Context triple: [Cutty Sark DLR station, railCode, CUT]
-
A.
CUT
CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
-
B.
Cuts
Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
-
C.
Cuts (TV series)
Cuts is an American sitcom that aired on UPN in the mid-2000s, focusing on the comedic ups and downs of running a family-owned barbershop in Baltimore.
-
D.
Gaillard Cut
Gaillard Cut is a historically significant, narrow, excavated channel through the Continental Divide in Panama that forms a key segment of the Panama Canal.
-
E.
Crosscut
Crosscut is a nonprofit, Seattle-based online news outlet known for its in-depth coverage of politics, public policy, and regional issues in the Pacific Northwest.
- 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: CUT Triple: [Cutty Sark DLR station, railCode, CUT]
Generated description
CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: CUT Target entity description: CUT is the National Rail station code assigned to Cutty Sark DLR station in London.
-
A.
CUT
CUT is a public university in Limassol, Cyprus, known for its focus on applied research and technology-oriented academic programs.
-
B.
Cuts
Cuts is an American television sitcom that aired on UPN, featuring Shannon Elizabeth in a comedic role set around a family-owned barbershop.
-
C.
Cuts (TV series)
Cuts is an American sitcom that aired on UPN in the mid-2000s, focusing on the comedic ups and downs of running a family-owned barbershop in Baltimore.
-
D.
Gaillard Cut
Gaillard Cut is a historically significant, narrow, excavated channel through the Continental Divide in Panama that forms a key segment of the Panama Canal.
-
E.
Crosscut
Crosscut is a nonprofit, Seattle-based online news outlet known for its in-depth coverage of politics, public policy, and regional issues in the Pacific Northwest.
- 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_69ab49e100c0819082a40cb797383243 |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abde91487881909989c08bbf76f0da |
completed | March 7, 2026, 8:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69afcead12588190bfbb2c9e93b05e0d |
completed | March 10, 2026, 7:56 a.m. |
| NEDg | Description generation | batch_69afcf5ec0a481909061d50877429f3b |
completed | March 10, 2026, 7:59 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69afcff778748190978e7d306e0d1ce1 |
completed | March 10, 2026, 8:01 a.m. |
Created at: March 6, 2026, 9:59 p.m.