Triple
T13855129
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Little Big Town |
E333044
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object |
Tornado
"Tornado" is a country music song by Little Big Town known for its dark, storm-themed metaphor and distinctive vocal harmonies.
|
E1066834
|
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: [Little Big Town, notableWork, Tornado]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tornado Context triple: [Little Big Town, notableWork, 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
Tornado is Zorro’s iconic black horse, known as his swift and loyal steed in the Zorro stories.
-
C.
Tornado
Tornado is a high-performance Python web framework and asynchronous networking library designed for handling large numbers of simultaneous connections.
-
D.
Tornado
The Tornado is a twin-engine, variable-sweep wing multirole combat aircraft developed jointly by the United Kingdom, Germany, and Italy, used for strike, reconnaissance, and electronic warfare missions.
-
E.
Toronado
The Toronado is a full-size personal luxury car produced by Oldsmobile, notable for pioneering front-wheel drive in American automobiles.
- 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: [Little Big Town, notableWork, Tornado]
Generated description
"Tornado" is a country music song by Little Big Town known for its dark, storm-themed metaphor and distinctive vocal harmonies.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tornado Target entity description: "Tornado" is a country music song by Little Big Town known for its dark, storm-themed metaphor and distinctive vocal harmonies.
-
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
Tornado is Zorro’s iconic black horse, known as his swift and loyal steed in the Zorro stories.
-
C.
Tornado
Tornado is a high-performance Python web framework and asynchronous networking library designed for handling large numbers of simultaneous connections.
-
D.
Tornado
The Tornado is a twin-engine, variable-sweep wing multirole combat aircraft developed jointly by the United Kingdom, Germany, and Italy, used for strike, reconnaissance, and electronic warfare missions.
-
E.
Toronado
The Toronado is a full-size personal luxury car produced by Oldsmobile, notable for pioneering front-wheel drive in American automobiles.
- 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_69d81c5ba13c8190839315f54768acfd |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de02db9c9c81909bb2d2fbfb7394b1 |
completed | April 14, 2026, 9:03 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c0fb7c3c819081fc6f89aa17d6af |
completed | May 3, 2026, 9:41 p.m. |
| NEDg | Description generation | batch_69f7c2c711948190ac614291592a7e03 |
completed | May 3, 2026, 9:48 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69f7c36f28b48190b734a9e5e7ae39b9 |
completed | May 3, 2026, 9:51 p.m. |
Created at: April 9, 2026, 10:14 p.m.