Triple
T1674337
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | William Cullen Bryant |
E36196
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Bryant
Bryant is a common English surname borne by numerous notable figures in American history, literature, sports, and public life.
|
E213940
|
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: Bryant | Statement: [William Cullen Bryant, familyName, Bryant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Bryant Context triple: [William Cullen Bryant, familyName, Bryant]
-
A.
Bryant
Bryant is the middle name of James B. Conant, the influential American chemist, educator, and president of Harvard University.
-
B.
Kobe Bryant
Kobe Bryant was an American professional basketball player, primarily with the Los Angeles Lakers, widely regarded as one of the greatest players in NBA history.
-
C.
Earvin
Earvin is the given first name of Magic Johnson, the legendary American basketball player and NBA Hall of Famer.
-
D.
Maye
Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
-
E.
Joe Bryant
Joe Bryant is a former American professional basketball player and coach, best known for his NBA career in the 1970s and 1980s and his later coaching roles in the U.S. and overseas.
- 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: Bryant Triple: [William Cullen Bryant, familyName, Bryant]
Generated description
Bryant is a common English surname borne by numerous notable figures in American history, literature, sports, and public life.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Bryant Target entity description: Bryant is a common English surname borne by numerous notable figures in American history, literature, sports, and public life.
-
A.
Bryant
Bryant is the middle name of James B. Conant, the influential American chemist, educator, and president of Harvard University.
-
B.
Kobe Bryant
Kobe Bryant was an American professional basketball player, primarily with the Los Angeles Lakers, widely regarded as one of the greatest players in NBA history.
-
C.
Earvin
Earvin is the given first name of Magic Johnson, the legendary American basketball player and NBA Hall of Famer.
-
D.
Maye
Maye is the first name of Maye Musk, a Canadian-South African model and dietitian known for her long-running fashion career and as the mother of entrepreneur Elon Musk.
-
E.
Joe Bryant
Joe Bryant is a former American professional basketball player and coach, best known for his NBA career in the 1970s and 1980s and his later coaching roles in the U.S. and overseas.
- 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_69a886139ed081909af0940aa9313512 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa6247ec408190bc25d694b3238fa4 |
completed | March 6, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69adeac637748190b67ddd9eedc3698d |
completed | March 8, 2026, 9:31 p.m. |
| NEDg | Description generation | batch_69adeb503ec88190b8d0cb17bbb8f520 |
completed | March 8, 2026, 9:34 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69adef13e030819086e9e8862198d859 |
completed | March 8, 2026, 9:50 p.m. |
Created at: March 4, 2026, 7:29 p.m.