Triple
T3993114
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Vicious |
E87037
|
entity |
| Predicate | productionCompany |
P490
|
FINISHED |
| Object |
Brown Eyed Boy
Brown Eyed Boy is a British television production company known for creating comedy and entertainment programming.
|
E404195
|
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: Brown Eyed Boy | Statement: [Vicious, productionCompany, Brown Eyed Boy]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Brown Eyed Boy Context triple: [Vicious, productionCompany, Brown Eyed Boy]
-
A.
This Boy
"This Boy" is a memoir by British politician Alan Johnson that recounts his impoverished childhood in post-war London.
-
B.
My Lovin' Eyes
"My Lovin' Eyes" is a song by singer-songwriter Carole King from her 1974 album *Wrap Around Joy*.
-
C.
In Your Eyes
In Your Eyes is a 2014 romantic science-fiction film written by Joss Whedon about two strangers who share a mysterious telepathic bond.
-
D.
In Your Eyes
"In Your Eyes" is a renowned 1986 pop-rock ballad by Peter Gabriel, celebrated for its emotional depth and iconic use in the film *Say Anything...*.
-
E.
In Your Eyes
"In Your Eyes" is a romantic ballad composed by Michael Masser, best known through George Benson’s soulful 1983 recording.
- 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: Brown Eyed Boy Triple: [Vicious, productionCompany, Brown Eyed Boy]
Generated description
Brown Eyed Boy is a British television production company known for creating comedy and entertainment programming.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Brown Eyed Boy Target entity description: Brown Eyed Boy is a British television production company known for creating comedy and entertainment programming.
-
A.
This Boy
"This Boy" is a memoir by British politician Alan Johnson that recounts his impoverished childhood in post-war London.
-
B.
My Lovin' Eyes
"My Lovin' Eyes" is a song by singer-songwriter Carole King from her 1974 album *Wrap Around Joy*.
-
C.
In Your Eyes
"In Your Eyes" is a renowned 1986 pop-rock ballad by Peter Gabriel, celebrated for its emotional depth and iconic use in the film *Say Anything...*.
-
D.
In Your Eyes
"In Your Eyes" is a romantic ballad composed by Michael Masser, best known through George Benson’s soulful 1983 recording.
-
E.
In Your Eyes
In Your Eyes is a 2014 romantic science-fiction film written by Joss Whedon about two strangers who share a mysterious telepathic bond.
- 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_69aed94118148190975e6aa4e554cde9 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefa1d9d8c8190982d092a73d38564 |
completed | March 9, 2026, 4:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5403970e08190bb491048b1bd7b16 |
completed | March 14, 2026, 11:02 a.m. |
| NEDg | Description generation | batch_69b54112e3788190800e295a745c4689 |
completed | March 14, 2026, 11:05 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69b541808d548190987ad1538c647664 |
completed | March 14, 2026, 11:07 a.m. |
Created at: March 9, 2026, 3:33 p.m.