Triple
T11397304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Diego Sockers |
E270009
|
entity |
| Predicate | hasNickname |
P39
|
FINISHED |
| Object |
Sockers
Sockers is the nickname of the San Diego Sockers, a professional indoor soccer team based in San Diego, California.
|
E923563
|
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: Sockers | Statement: [San Diego Sockers, hasNickname, Sockers]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sockers Context triple: [San Diego Sockers, hasNickname, Sockers]
-
A.
Socks
Socks is a fictional character, likely an animal companion or pet, featured in the "Dear Socks, Dear Buddy" book.
-
B.
Coogs
Coogs is a common shorthand nickname for the University of Houston Cougars athletic teams and their fans.
-
C.
Chubbies Shorts
Chubbies Shorts is a casual apparel brand best known for its retro-inspired, brightly colored men's shorts and laid-back lifestyle marketing.
-
D.
Keds
Keds is an American footwear brand best known for its classic canvas sneakers and long association with casual, everyday fashion.
-
E.
Sneakers
"Sneakers" is a 1992 comedic heist thriller film about a team of security experts who become entangled in espionage over a powerful code-breaking device.
- 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: Sockers Triple: [San Diego Sockers, hasNickname, Sockers]
Generated description
Sockers is the nickname of the San Diego Sockers, a professional indoor soccer team based in San Diego, California.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sockers Target entity description: Sockers is the nickname of the San Diego Sockers, a professional indoor soccer team based in San Diego, California.
-
A.
Socks
Socks is a fictional character, likely an animal companion or pet, featured in the "Dear Socks, Dear Buddy" book.
-
B.
Coogs
Coogs is a common shorthand nickname for the University of Houston Cougars athletic teams and their fans.
-
C.
Chubbies Shorts
Chubbies Shorts is a casual apparel brand best known for its retro-inspired, brightly colored men's shorts and laid-back lifestyle marketing.
-
D.
Keds
Keds is an American footwear brand best known for its classic canvas sneakers and long association with casual, everyday fashion.
-
E.
Sneakers
"Sneakers" is a 1992 comedic heist thriller film about a team of security experts who become entangled in espionage over a powerful code-breaking device.
- 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_69d6aacdbc6c8190af6dc3d5f5d22836 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d80019d3d48190a2f473deb6eae33a |
completed | April 9, 2026, 7:38 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e58cd74280819092f8c420630f4889 |
completed | April 20, 2026, 2:17 a.m. |
| NEDg | Description generation | batch_69e59774e6648190a38b2515a83c2e0c |
completed | April 20, 2026, 3:03 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69e5a3abf24481908fb71f4ef6b13532 |
completed | April 20, 2026, 3:55 a.m. |
Created at: April 8, 2026, 9:34 p.m.