Triple
T7501970
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | EMC Corporation |
E177281
|
entity |
| Predicate | foundedBy |
P104
|
FINISHED |
| Object |
John Curly
John Curly is a technology executive best known as a co-founder of EMC Corporation, a major data storage and information management company.
|
E668692
|
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: John Curly | Statement: [EMC Corporation, foundedBy, John Curly]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: John Curly Context triple: [EMC Corporation, foundedBy, John Curly]
-
A.
Curly McLain
Curly McLain is the charming cowboy protagonist of the classic Rodgers and Hammerstein musical "Oklahoma!"
-
B.
Dick Hogan
Dick Hogan was an American actor best remembered for his role in Alfred Hitchcock’s 1948 thriller "Rope."
-
C.
Tom Canty
Tom Canty is the impoverished London boy who swaps identities with Prince Edward in Mark Twain’s novel "The Prince and the Pauper," highlighting themes of class and social injustice.
-
D.
Errol
Errol is a masculine given name of English origin, often used as a first name in various English-speaking countries.
-
E.
Nat Hickey
Nat Hickey was an early professional basketball player and coach best known for briefly appearing in an NBA game at age 45, making him the oldest player in league history.
- 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: John Curly Triple: [EMC Corporation, foundedBy, John Curly]
Generated description
John Curly is a technology executive best known as a co-founder of EMC Corporation, a major data storage and information management company.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: John Curly Target entity description: John Curly is a technology executive best known as a co-founder of EMC Corporation, a major data storage and information management company.
-
A.
Curly McLain
Curly McLain is the charming cowboy protagonist of the classic Rodgers and Hammerstein musical "Oklahoma!"
-
B.
Dick Hogan
Dick Hogan was an American actor best remembered for his role in Alfred Hitchcock’s 1948 thriller "Rope."
-
C.
Tom Canty
Tom Canty is the impoverished London boy who swaps identities with Prince Edward in Mark Twain’s novel "The Prince and the Pauper," highlighting themes of class and social injustice.
-
D.
Errol
Errol is a masculine given name of English origin, often used as a first name in various English-speaking countries.
-
E.
Nat Hickey
Nat Hickey was an early professional basketball player and coach best known for briefly appearing in an NBA game at age 45, making him the oldest player in league history.
- 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_69c69f2696688190915a8458f2398211 |
completed | March 27, 2026, 3:15 p.m. |
| NER | Named-entity recognition | batch_69c6f59be2748190ad8e94179f594e51 |
completed | March 27, 2026, 9:24 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c83c9490fc81908d35c0537b45aa13 |
completed | March 28, 2026, 8:39 p.m. |
| NEDg | Description generation | batch_69c83e17c25c8190a7a329f0a6169fac |
completed | March 28, 2026, 8:46 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c83ef9ce408190907a62c9d0a6dc16 |
completed | March 28, 2026, 8:50 p.m. |
Created at: March 27, 2026, 3:44 p.m.