Triple
T14240153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Boy with the Topknot |
E352982
|
entity |
| Predicate | screenwriter |
P2831
|
FINISHED |
| Object |
Mick Ford
Mick Ford is a British screenwriter and actor known for adapting works such as "The Boy with the Topknot" for television.
|
E1091020
|
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: Mick Ford | Statement: [The Boy with the Topknot, screenwriter, Mick Ford]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Mick Ford Context triple: [The Boy with the Topknot, screenwriter, Mick Ford]
-
A.
Mick Farmer
Mick Farmer is a notable individual distinguished enough in his field or public life to be recognized as a prominent bearer of the surname Farmer.
-
B.
Mick Ward
Mick Ward is a musician best known for his work with the band Kingfish.
-
C.
Mick Rogers
Mick Rogers is an Australian former professional road cyclist known for his time-trialling strength and multiple world championship titles in the team time trial.
-
D.
Mick Shipman
Mick Shipman is a down-to-earth, good-natured family man and father figure in the British sitcom "Gavin & Stacey."
-
E.
Ronald Drever
Ronald Drever was a Scottish experimental physicist best known as a co-founder of the Laser Interferometer Gravitational-Wave Observatory (LIGO) and a pioneer in the detection of gravitational waves.
- 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: Mick Ford Triple: [The Boy with the Topknot, screenwriter, Mick Ford]
Generated description
Mick Ford is a British screenwriter and actor known for adapting works such as "The Boy with the Topknot" for television.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Mick Ford Target entity description: Mick Ford is a British screenwriter and actor known for adapting works such as "The Boy with the Topknot" for television.
-
A.
Mick Farmer
Mick Farmer is a notable individual distinguished enough in his field or public life to be recognized as a prominent bearer of the surname Farmer.
-
B.
Mick Ward
Mick Ward is a musician best known for his work with the band Kingfish.
-
C.
Mick Rogers
Mick Rogers is an Australian former professional road cyclist known for his time-trialling strength and multiple world championship titles in the team time trial.
-
D.
Mick Shipman
Mick Shipman is a down-to-earth, good-natured family man and father figure in the British sitcom "Gavin & Stacey."
-
E.
Ronald Drever
Ronald Drever was a Scottish experimental physicist best known as a co-founder of the Laser Interferometer Gravitational-Wave Observatory (LIGO) and a pioneer in the detection of gravitational waves.
- 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_69d8278adc7c8190a9218d69bce3c4e6 |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de62432fb48190b153805b85c4f2d2 |
completed | April 14, 2026, 3:50 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd3d1081148190b8830615a34711c0 |
completed | May 8, 2026, 1:32 a.m. |
| NEDg | Description generation | batch_69fd3f09579081908b229d0ad9befea3 |
completed | May 8, 2026, 1:40 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fd3f5763e48190a4482cc01774adf4 |
completed | May 8, 2026, 1:41 a.m. |
Created at: April 10, 2026, 1:08 a.m.