Triple
T22288358
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lingerie Football League |
E550922
|
entity |
| Predicate | basedOn |
P98
|
FINISHED |
| Object |
Lingerie Bowl
Lingerie Bowl is an annual alternative Super Bowl halftime event featuring women playing full-contact American football in lingerie-style uniforms.
|
E1528448
|
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: Lingerie Bowl | Statement: [Lingerie Football League, basedOn, Lingerie Bowl]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lingerie Bowl Context triple: [Lingerie Football League, basedOn, Lingerie Bowl]
-
A.
The Lingerie Shop
The Lingerie Shop is a comedic sketch from the British television series Monty Python's Flying Circus, known for its absurd and surreal humor.
-
B.
Milk Cup
The Milk Cup was the sponsored name for the English Football League Cup during the 1980s, reflecting its title sponsorship by the Milk Marketing Board.
-
C.
Biskinik
Biskinik is the official newspaper of the Choctaw Nation, providing news, cultural information, and community updates for Choctaw citizens.
-
D.
Bündchen
Bündchen is the German-origin surname most famously borne by Brazilian supermodel Gisele Bündchen.
-
E.
Nippletop
Nippletop is a prominent Adirondack High Peak in New York’s High Peaks Wilderness, known for its steep ascent and expansive summit views.
- 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: Lingerie Bowl Triple: [Lingerie Football League, basedOn, Lingerie Bowl]
Generated description
Lingerie Bowl is an annual alternative Super Bowl halftime event featuring women playing full-contact American football in lingerie-style uniforms.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Lingerie Bowl Target entity description: Lingerie Bowl is an annual alternative Super Bowl halftime event featuring women playing full-contact American football in lingerie-style uniforms.
-
A.
The Lingerie Shop
The Lingerie Shop is a comedic sketch from the British television series Monty Python's Flying Circus, known for its absurd and surreal humor.
-
B.
Milk Cup
The Milk Cup was the sponsored name for the English Football League Cup during the 1980s, reflecting its title sponsorship by the Milk Marketing Board.
-
C.
Biskinik
Biskinik is the official newspaper of the Choctaw Nation, providing news, cultural information, and community updates for Choctaw citizens.
-
D.
Bündchen
Bündchen is the German-origin surname most famously borne by Brazilian supermodel Gisele Bündchen.
-
E.
Nippletop
Nippletop is a prominent Adirondack High Peak in New York’s High Peaks Wilderness, known for its steep ascent and expansive summit views.
- 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f15609854c81908adb7681cff2c404 |
completed | April 29, 2026, 12:51 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a0abcadc3e081908e98e6810b3cba6e |
completed | May 18, 2026, 7:15 a.m. |
| NEDg | Description generation | batch_6a0abda9a0f08190945fbf26bf893642 |
completed | May 18, 2026, 7:20 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a0abef28a9481908c67d1eb401147d4 |
completed | May 18, 2026, 7:25 a.m. |
Created at: April 16, 2026, 8:41 p.m.