Triple
T6820683
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1st Viscount Slim |
E156889
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Slim
Slim is a surname most notably associated with William Slim, 1st Viscount Slim, a prominent British military commander and statesman of the 20th century.
|
E560432
|
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: Slim | Statement: [1st Viscount Slim, familyName, Slim]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Slim Context triple: [1st Viscount Slim, familyName, Slim]
-
A.
Slim
Slim is the tall, sarcastic stick insect who performs as a reluctant clown in the circus troupe in Pixar's animated film "A Bug's Life."
-
B.
Slim
Slim is a highly respected, compassionate, and insightful mule driver on the ranch in John Steinbeck’s novel "Of Mice and Men," often serving as a moral authority among the workers.
-
C.
Slim
Slim is a lightweight Ruby templating engine known for its minimal syntax and fast rendering performance.
-
D.
Slim
Slim is the nickname of Slim Keith, a prominent American socialite and fashion icon of the mid-20th century known for her influence in high society and style.
-
E.
Slim
Slim is a nickname for Cyclops, the optic-blasting mutant leader of the X-Men in Marvel Comics.
- 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: Slim Triple: [1st Viscount Slim, familyName, Slim]
Generated description
Slim is a surname most notably associated with William Slim, 1st Viscount Slim, a prominent British military commander and statesman of the 20th century.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Slim Target entity description: Slim is a surname most notably associated with William Slim, 1st Viscount Slim, a prominent British military commander and statesman of the 20th century.
-
A.
Slim
chosen
Slim is the surname of Bill Slim, a prominent British field marshal who played a key leadership role in the Burma Campaign during World War II.
-
B.
Slim
Slim is the nickname of Slim Keith, a prominent American socialite and fashion icon of the mid-20th century known for her influence in high society and style.
-
C.
Slim
Slim is a nickname for Cyclops, the optic-blasting mutant leader of the X-Men in Marvel Comics.
-
D.
Slim
Slim is a lightweight Ruby templating engine known for its minimal syntax and fast rendering performance.
-
E.
Slim
Slim is a highly respected, compassionate, and insightful mule driver on the ranch in John Steinbeck’s novel "Of Mice and Men," often serving as a moral authority among the workers.
- F. None of above.
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_69c688298a288190af3f285d57f76bbe |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6d359176c8190a34664ba2fcf7ee2 |
completed | March 27, 2026, 6:58 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c723e797908190bb0a2d22556b5906 |
completed | March 28, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69c724e915dc8190a82b69939f78420d |
completed | March 28, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c728ddadd881909c2faa435031a635 |
completed | March 28, 2026, 1:03 a.m. |
Created at: March 27, 2026, 2:17 p.m.