Triple
T22288426
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | LFL |
E550924
|
entity |
| Predicate | team |
P3756
|
FINISHED |
| Object |
Dallas Desire
Dallas Desire was a women's American football team that competed in the Legends Football League, known for its lingerie-style uniforms and arena-style play.
|
E1528461
|
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: Dallas Desire | Statement: [LFL, team, Dallas Desire]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Dallas Desire Context triple: [LFL, team, Dallas Desire]
-
A.
Uptown Dallas
Uptown Dallas is a vibrant, upscale neighborhood just north of downtown Dallas known for its high-rise living, trendy restaurants, nightlife, and walkable urban atmosphere.
-
B.
Sweetheart City
Sweetheart City is a romantic nickname for Loveland, Colorado, known for its Valentine’s Day traditions and heart-themed celebrations.
-
C.
Sugar Land
Sugar Land is a rapidly growing suburban city in the Houston metropolitan area, known for its master-planned communities, high quality of life, and strong local economy.
-
D.
H-Town
H-Town is a common nickname for the city of Huntington in the U.S. state of West Virginia.
-
E.
H-Town
H-Town is a popular nickname for the city of Houston, Texas, often used in reference to its culture, music, and sports communities.
- 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: Dallas Desire Triple: [LFL, team, Dallas Desire]
Generated description
Dallas Desire was a women's American football team that competed in the Legends Football League, known for its lingerie-style uniforms and arena-style play.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Dallas Desire Target entity description: Dallas Desire was a women's American football team that competed in the Legends Football League, known for its lingerie-style uniforms and arena-style play.
-
A.
Uptown Dallas
Uptown Dallas is a vibrant, upscale neighborhood just north of downtown Dallas known for its high-rise living, trendy restaurants, nightlife, and walkable urban atmosphere.
-
B.
Sweetheart City
Sweetheart City is a romantic nickname for Loveland, Colorado, known for its Valentine’s Day traditions and heart-themed celebrations.
-
C.
Sugar Land
Sugar Land is a rapidly growing suburban city in the Houston metropolitan area, known for its master-planned communities, high quality of life, and strong local economy.
-
D.
H-Town
H-Town is a common nickname for the city of Huntington in the U.S. state of West Virginia.
-
E.
H-Town
H-Town is a popular nickname for the city of Houston, Texas, often used in reference to its culture, music, and sports communities.
- 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.