Triple
T5313296
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | InterCityExpress |
E119084
|
entity |
| Predicate | rollingStockFamily |
P45556
|
FINISHED |
| Object |
ICE TD
ICE TD is a diesel-powered variant of Germany’s high-speed InterCityExpress train series designed for routes without full electrification.
|
E510346
|
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: ICE TD | Statement: [InterCityExpress, rollingStockFamily, ICE TD]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: ICE TD Context triple: [InterCityExpress, rollingStockFamily, ICE TD]
-
A.
Terrell
Terrell is a masculine given name most notably associated with American athletes, particularly in professional football and basketball.
-
B.
Brady
Brady is a common English surname of Irish origin, borne by numerous notable figures in sports, entertainment, and public life.
-
C.
Michael Vick
Michael Vick is a former NFL quarterback best known for his electrifying dual-threat playmaking ability, particularly during his early career with the Atlanta Falcons.
-
D.
Tildon
Tildon is a less common variant of the given name Tilden, typically used as a masculine first name.
-
E.
Brady Bill
The Brady Bill is a U.S. federal law that established background checks and waiting periods for handgun purchases to help prevent gun violence.
- 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: ICE TD Triple: [InterCityExpress, rollingStockFamily, ICE TD]
Generated description
ICE TD is a diesel-powered variant of Germany’s high-speed InterCityExpress train series designed for routes without full electrification.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: ICE TD Target entity description: ICE TD is a diesel-powered variant of Germany’s high-speed InterCityExpress train series designed for routes without full electrification.
-
A.
Terrell
Terrell is a masculine given name most notably associated with American athletes, particularly in professional football and basketball.
-
B.
Brady
Brady is a common English surname of Irish origin, borne by numerous notable figures in sports, entertainment, and public life.
-
C.
Michael Vick
Michael Vick is a former NFL quarterback best known for his electrifying dual-threat playmaking ability, particularly during his early career with the Atlanta Falcons.
-
D.
Tildon
Tildon is a less common variant of the given name Tilden, typically used as a masculine first name.
-
E.
Brady Bill
The Brady Bill is a U.S. federal law that established background checks and waiting periods for handgun purchases to help prevent gun violence.
- 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_69bd446b57bc8190a513d2e6c40314f3 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd8536c06c81908ef8ba8c39b4fa30 |
completed | March 20, 2026, 5:34 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69bf1106ef9c8190811f7b70e784c962 |
completed | March 21, 2026, 9:43 p.m. |
| NEDg | Description generation | batch_69bf11a601c481908a8cb6ea2c04d6df |
completed | March 21, 2026, 9:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69bf127799208190a47580ed7b9ad550 |
completed | March 21, 2026, 9:49 p.m. |
Created at: March 20, 2026, 1:54 p.m.