Triple
T4170940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zorro |
E84559
|
entity |
| Predicate | vehicle |
P7735
|
FINISHED |
| Object |
Tornado
Tornado is Zorro’s iconic black horse, known as his swift and loyal steed in the Zorro stories.
|
E417917
|
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: Tornado | Statement: [Zorro, vehicle, Tornado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tornado Context triple: [Zorro, vehicle, Tornado]
-
A.
Tornado
Tornado is a high-thrill water slide attraction featuring steep drops and a large funnel element, located at the Wet'n'Wild Gold Coast water park in Australia.
-
B.
Tornado F3
The Tornado F3 is a British twin-engine, two-seat air defense variant of the Panavia Tornado fighter aircraft, designed primarily for long-range interception missions.
-
C.
Tennessee Tornado
Tennessee Tornado is a steel looping roller coaster at Dollywood known for its intense drops, smooth inversions, and Appalachian mine-themed setting.
-
D.
Cyclone
Cyclone is the nickname of early 20th-century Canadian ice hockey legend Cyclone Taylor, renowned as one of the sport’s first great rushing defensemen.
-
E.
Cyclone
Cyclone is a statically typed, safe dialect of C designed to prevent common programming errors such as buffer overflows and memory leaks while retaining low-level control.
- 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: Tornado Triple: [Zorro, vehicle, Tornado]
Generated description
Tornado is Zorro’s iconic black horse, known as his swift and loyal steed in the Zorro stories.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tornado Target entity description: Tornado is Zorro’s iconic black horse, known as his swift and loyal steed in the Zorro stories.
-
A.
Tornado
Tornado is a high-thrill water slide attraction featuring steep drops and a large funnel element, located at the Wet'n'Wild Gold Coast water park in Australia.
-
B.
Tornado F3
The Tornado F3 is a British twin-engine, two-seat air defense variant of the Panavia Tornado fighter aircraft, designed primarily for long-range interception missions.
-
C.
Tennessee Tornado
Tennessee Tornado is a steel looping roller coaster at Dollywood known for its intense drops, smooth inversions, and Appalachian mine-themed setting.
-
D.
Cyclone
Cyclone is the nickname of early 20th-century Canadian ice hockey legend Cyclone Taylor, renowned as one of the sport’s first great rushing defensemen.
-
E.
Cyclone
Cyclone is a statically typed, safe dialect of C designed to prevent common programming errors such as buffer overflows and memory leaks while retaining low-level control.
- 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_69aed932cab48190b80ffe35f7029ae1 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69af02c87cc88190a9ec3712db18a8a7 |
completed | March 9, 2026, 5:26 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b57f4ef1a08190a232ed94595a86e8 |
completed | March 14, 2026, 3:31 p.m. |
| NEDg | Description generation | batch_69b580e08e888190b48ddae4435c984a |
completed | March 14, 2026, 3:38 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69b5817b52bc8190aba6863a9ef05acf |
completed | March 14, 2026, 3:40 p.m. |
Created at: March 9, 2026, 3:45 p.m.