Triple
T23559361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Whitman Mayo |
E579188
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Whitman |
—
|
NE NERFINISHED |
How this triple was built (2 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: Whitman | Statement: [Whitman Mayo, givenName, Whitman]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Whitman Context triple: [Whitman Mayo, givenName, Whitman]
-
A.
Whitman
Whitman is a residential neighborhood in South Philadelphia, Pennsylvania, known for its rowhomes, diverse community, and proximity to the Delaware River waterfront.
-
B.
Whitman
Whitman is a small town in Plymouth County, Massachusetts, known as the birthplace of the chocolate chip cookie.
-
C.
Whitman
chosen
Whitman is a common English-language surname borne by various notable figures in literature, arts, and public life.
-
D.
Walt Whitman
Walt Whitman was an American character actor of the silent film era, known for his supporting roles in numerous early 20th-century motion pictures.
-
E.
Walt Whitman
Walt Whitman was a pioneering 19th-century American poet and essayist best known for his groundbreaking poetry collection "Leaves of Grass," which profoundly influenced modern literature.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e245fe24588190888f3aec8407d8e3 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1af672db4819087dbff2c0dfadd7f |
completed | April 29, 2026, 7:12 a.m. |
Created at: April 17, 2026, 6:12 p.m.