Triple
T20195251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | I'm Walkin' |
E493066
|
entity |
| Predicate | hasPerformer |
P5936
|
FINISHED |
| Object |
Frank Fields
Frank Fields was an American rhythm and blues bassist known for his session work in New Orleans during the 1950s and 1960s.
|
E1416464
|
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: Frank Fields | Statement: [I'm Walkin', hasPerformer, Frank Fields]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Frank Fields Context triple: [I'm Walkin', hasPerformer, Frank Fields]
-
A.
Stan Fields
Stan Fields is a fictional beauty pageant host and commentator featured in the comedy film series "Miss Congeniality."
-
B.
J. C. Fields
J. C. Fields was a Canadian mathematician best known for founding the Fields Medal, one of the most prestigious awards in mathematics.
-
C.
Harry Fielder
Harry Fielder was a British character actor and extra known for his numerous small roles in film and television, including appearances in major productions like Star Wars and Doctor Who.
-
D.
Joseph Fields
Joseph Fields was an American playwright, screenwriter, and producer known for his work on Broadway and in Hollywood during the mid-20th century.
-
E.
Jack Fields
Jack Fields was the first husband of American actress and television producer Whitney Blake.
- 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: Frank Fields Triple: [I'm Walkin', hasPerformer, Frank Fields]
Generated description
Frank Fields was an American rhythm and blues bassist known for his session work in New Orleans during the 1950s and 1960s.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Frank Fields Target entity description: Frank Fields was an American rhythm and blues bassist known for his session work in New Orleans during the 1950s and 1960s.
-
A.
Stan Fields
Stan Fields is a fictional beauty pageant host and commentator featured in the comedy film series "Miss Congeniality."
-
B.
J. C. Fields
J. C. Fields was a Canadian mathematician best known for founding the Fields Medal, one of the most prestigious awards in mathematics.
-
C.
Harry Fielder
Harry Fielder was a British character actor and extra known for his numerous small roles in film and television, including appearances in major productions like Star Wars and Doctor Who.
-
D.
Joseph Fields
Joseph Fields was an American playwright, screenwriter, and producer known for his work on Broadway and in Hollywood during the mid-20th century.
-
E.
Jack Fields
Jack Fields was the first husband of American actress and television producer Whitney Blake.
- 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_69da6268a034819081cbd9ea5a1c9475 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66ad8b3cc8190aa9c9c79c552002a |
completed | April 20, 2026, 6:05 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a083c8a440c819089f0d90aacc640b5 |
completed | May 16, 2026, 9:44 a.m. |
| NEDg | Description generation | batch_6a083d95db488190b2ffafc7e0d874dc |
completed | May 16, 2026, 9:49 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a083e12d31481909295a5dc4e47b14b |
completed | May 16, 2026, 9:51 a.m. |
Created at: April 11, 2026, 11:37 p.m.