Triple
T3353719
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ian McShane |
E70555
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Hot Rod
Hot Rod is a 2007 comedy film about an inept amateur stuntman who plans an outrageous motorcycle jump to earn respect and save his stepfather.
|
E96554
|
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: Hot Rod | Statement: [Ian McShane, notableWork, Hot Rod]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hot Rod Context triple: [Ian McShane, notableWork, Hot Rod]
-
A.
Hot Rod
Hot Rod is a 2007 comedy film starring Andy Samberg as an inept stuntman attempting a massive jump to earn money for his stepfather’s surgery.
-
B.
Red Duster
The Red Duster is the traditional British civil ensign, a red flag with the Union Jack in the canton historically flown by British merchant ships.
-
C.
L’Auto
L’Auto was a French sports newspaper best known for creating and organizing the Tour de France.
-
D.
Westy
Westy was the widely used nickname of General William Westmoreland, the U.S. Army officer who commanded American forces during the Vietnam War.
-
E.
Mack Rides
Mack Rides is a German amusement ride manufacturer known for designing and building roller coasters and other attractions for theme parks worldwide.
- 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: Hot Rod Triple: [Ian McShane, notableWork, Hot Rod]
Generated description
Hot Rod is a 2007 comedy film about an inept amateur stuntman who plans an outrageous motorcycle jump to earn respect and save his stepfather.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hot Rod Target entity description: Hot Rod is a 2007 comedy film about an inept amateur stuntman who plans an outrageous motorcycle jump to earn respect and save his stepfather.
-
A.
Hot Rod
chosen
Hot Rod is a 2007 comedy film starring Andy Samberg as an inept stuntman attempting a massive jump to earn money for his stepfather’s surgery.
-
B.
Red Duster
The Red Duster is the traditional British civil ensign, a red flag with the Union Jack in the canton historically flown by British merchant ships.
-
C.
L’Auto
L’Auto was a French sports newspaper best known for creating and organizing the Tour de France.
-
D.
Westy
Westy was the widely used nickname of General William Westmoreland, the U.S. Army officer who commanded American forces during the Vietnam War.
-
E.
Mack Rides
Mack Rides is a German amusement ride manufacturer known for designing and building roller coasters and other attractions for theme parks worldwide.
- F. None of above.
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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb24036848190bac779d17dfdce3b |
completed | March 8, 2026, 5:30 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b325373a1c8190b26d883e2f0dd92b |
completed | March 12, 2026, 8:42 p.m. |
| NEDg | Description generation | batch_69b329016c7c819098b494ae5d712036 |
completed | March 12, 2026, 8:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b329aca800819091f287a2f00557a2 |
completed | March 12, 2026, 9:01 p.m. |
Created at: March 8, 2026, 3:13 p.m.