Triple
T16932912
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melvin B. Tolson |
E410756
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Tolson
Tolson is a surname most notably associated with Melvin B. Tolson, an influential American poet, educator, and civil rights advocate.
|
E1241549
|
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: Tolson | Statement: [Melvin B. Tolson, familyName, Tolson]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tolson Context triple: [Melvin B. Tolson, familyName, Tolson]
-
A.
Burkley
Burkley is a surname most notably associated with American character actor Dennis Burkley.
-
B.
Warley
Warley is a locality within the Brentwood Borough of Essex, England, known primarily as a residential suburb with historical military and institutional connections.
-
C.
Sharswood
Sharswood is a residential neighborhood in North Philadelphia known for its ongoing redevelopment and proximity to areas like Brewerytown and Girard College.
-
D.
Conley
Conley is a surname most prominently associated with NBA point guard Mike Conley Jr.
-
E.
Toland
Toland is a surname most notably associated with Gregg Toland, the pioneering American cinematographer renowned for his innovative deep-focus techniques in films like "Citizen Kane."
- 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: Tolson Triple: [Melvin B. Tolson, familyName, Tolson]
Generated description
Tolson is a surname most notably associated with Melvin B. Tolson, an influential American poet, educator, and civil rights advocate.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tolson Target entity description: Tolson is a surname most notably associated with Melvin B. Tolson, an influential American poet, educator, and civil rights advocate.
-
A.
Burkley
Burkley is a surname most notably associated with American character actor Dennis Burkley.
-
B.
Warley
Warley is a locality within the Brentwood Borough of Essex, England, known primarily as a residential suburb with historical military and institutional connections.
-
C.
Sharswood
Sharswood is a residential neighborhood in North Philadelphia known for its ongoing redevelopment and proximity to areas like Brewerytown and Girard College.
-
D.
Conley
Conley is a surname most prominently associated with NBA point guard Mike Conley Jr.
-
E.
Toland
Toland is a surname most notably associated with Gregg Toland, the pioneering American cinematographer renowned for his innovative deep-focus techniques in films like "Citizen Kane."
- 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_69d886c886688190967be07322597ac9 |
completed | April 10, 2026, 5:12 a.m. |
| NER | Named-entity recognition | batch_69e3cf2650e08190b669d0cf2cf1275b |
completed | April 18, 2026, 6:36 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a00cfe0ff608190903d0e64e04b1550 |
completed | May 10, 2026, 6:35 p.m. |
| NEDg | Description generation | batch_6a00d0ee2c4481908de08c552a8cbcfc |
completed | May 10, 2026, 6:39 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a00d15d5be081908387de6ec6d061f5 |
completed | May 10, 2026, 6:41 p.m. |
Created at: April 10, 2026, 5:30 a.m.