Triple
T1801050
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wisdom |
E39718
|
entity |
| Predicate | hasNotableBearer |
P458
|
FINISHED |
| Object |
Tom Wisdom
Tom Wisdom is a British actor known for his roles in films like "300" and various television dramas.
|
E201469
|
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: Tom Wisdom | Statement: [Wisdom, hasNotableBearer, Tom Wisdom]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tom Wisdom Context triple: [Wisdom, hasNotableBearer, Tom Wisdom]
-
A.
Wes Wise
Wes Wise is an American journalist and politician who served as mayor of Dallas, Texas, in the 1970s.
-
B.
Tom Solomon
Tom Solomon is the affable, commitment-tested protagonist of the romantic comedy film "The Five-Year Engagement," whose prolonged engagement drives the story’s humor and heart.
-
C.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
-
D.
Malcolm Smith
Malcolm Smith is an American former NFL linebacker best known for his standout performance with the Seattle Seahawks, including earning Super Bowl XLVIII Most Valuable Player honors.
-
E.
Charlie Smith
Charlie Smith is a fictional protagonist featured as the central character in a narrative work.
- 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: Tom Wisdom Triple: [Wisdom, hasNotableBearer, Tom Wisdom]
Generated description
Tom Wisdom is a British actor known for his roles in films like "300" and various television dramas.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tom Wisdom Target entity description: Tom Wisdom is a British actor known for his roles in films like "300" and various television dramas.
-
A.
Wes Wise
Wes Wise is an American journalist and politician who served as mayor of Dallas, Texas, in the 1970s.
-
B.
Tom Solomon
Tom Solomon is the affable, commitment-tested protagonist of the romantic comedy film "The Five-Year Engagement," whose prolonged engagement drives the story’s humor and heart.
-
C.
Wesley Saunders
Wesley Saunders is an American basketball player best known for starring as a versatile guard/forward for Harvard University, where he became one of the program’s top performers in the early 2010s.
-
D.
Malcolm Smith
Malcolm Smith is an American former NFL linebacker best known for his standout performance with the Seattle Seahawks, including earning Super Bowl XLVIII Most Valuable Player honors.
-
E.
Charlie Smith
Charlie Smith is a fictional protagonist featured as the central character in a narrative work.
- 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_69a88632aa588190ba3978fde0db5bbd |
completed | March 4, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69aa656ad5d4819090e677ad137b0cd1 |
completed | March 6, 2026, 5:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adb5db1c7c81908c25e62dca1cb825 |
completed | March 8, 2026, 5:46 p.m. |
| NEDg | Description generation | batch_69adb8b626688190b4953d4549339dea |
completed | March 8, 2026, 5:58 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adb9253fa08190bfb7d245208150c0 |
completed | March 8, 2026, 6 p.m. |
Created at: March 4, 2026, 7:32 p.m.