Triple
T20124078
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | F.Y.P |
E490697
|
entity |
| Predicate | hasMember |
P10
|
FINISHED |
| Object |
Chris Fields
Chris Fields is a musician best known as a member of the punk rock band F.Y.P (Five Year Plan).
|
E1413186
|
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: Chris Fields | Statement: [F.Y.P, hasMember, Chris Fields]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chris Fields Context triple: [F.Y.P, hasMember, Chris Fields]
-
A.
Christopher John Fields
Christopher John Fields is an American actor best known for his supporting role in the science fiction horror film "Alien 3."
-
B.
Kevin Fields
Kevin Fields is the male lead in the romantic comedy film "Monster-in-Law," serving as the love interest whose engagement triggers the central conflict between his fiancée and his overbearing mother.
-
C.
Stan Fields
Stan Fields is a fictional beauty pageant host and commentator featured in the comedy film series "Miss Congeniality."
-
D.
Bruce Fielder
Bruce Fielder, better known by his stage name Sigala, is a British DJ, record producer, and songwriter recognized for his upbeat electronic dance music hits.
-
E.
Adam Fields
Adam Fields is a film producer known for his work on various Hollywood movies, including the comedy "The Wedding Ringer."
- 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: Chris Fields Triple: [F.Y.P, hasMember, Chris Fields]
Generated description
Chris Fields is a musician best known as a member of the punk rock band F.Y.P (Five Year Plan).
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Chris Fields Target entity description: Chris Fields is a musician best known as a member of the punk rock band F.Y.P (Five Year Plan).
-
A.
Christopher John Fields
Christopher John Fields is an American actor best known for his supporting role in the science fiction horror film "Alien 3."
-
B.
Kevin Fields
Kevin Fields is the male lead in the romantic comedy film "Monster-in-Law," serving as the love interest whose engagement triggers the central conflict between his fiancée and his overbearing mother.
-
C.
Stan Fields
Stan Fields is a fictional beauty pageant host and commentator featured in the comedy film series "Miss Congeniality."
-
D.
Bruce Fielder
Bruce Fielder, better known by his stage name Sigala, is a British DJ, record producer, and songwriter recognized for his upbeat electronic dance music hits.
-
E.
Adam Fields
Adam Fields is a film producer known for his work on various Hollywood movies, including the comedy "The Wedding Ringer."
- 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_69da62651a0c8190a3e05e95e056a66b |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e6674054188190a15d55a73e86d143 |
completed | April 20, 2026, 5:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a082dd7d19481908fed99f3c37b91bf |
completed | May 16, 2026, 8:42 a.m. |
| NEDg | Description generation | batch_6a082f03be608190a68d27656d33fe5e |
completed | May 16, 2026, 8:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_6a082faf0ca48190a498079bda6fb96f |
completed | May 16, 2026, 8:49 a.m. |
Created at: April 11, 2026, 11:30 p.m.