Triple
T8120000
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cicely Tyson |
E189580
|
entity |
| Predicate | notableWork |
P4
|
FINISHED |
| Object | Sounder |
E659779
|
NE FINISHED |
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: Sounder | Statement: [Cicely Tyson, notableWork, Sounder]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sounder Context triple: [Cicely Tyson, notableWork, Sounder]
-
A.
Sounder
chosen
Sounder is a 1972 American drama film about an African American sharecropping family in the Great Depression, acclaimed for its powerful storytelling and performances.
-
B.
Sounder
Sounder is a regional commuter rail service in the Seattle metropolitan area operated by Sound Transit, providing weekday passenger trains primarily between Seattle, Tacoma, and Everett.
-
C.
The Learning Tree
The Learning Tree is a semi-autobiographical novel by Gordon Parks that portrays an African American boy’s coming-of-age in 1920s Kansas amid racism and moral conflict.
-
D.
Sula
Sula is a coastal municipality in Møre og Romsdal county, Norway, known for its fishing industry, maritime heritage, and scenic island landscapes.
-
E.
Sula
Sula is a genus of large seabirds known as boobies, characterized by their strong diving ability and predominantly tropical oceanic distribution.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82bb74848190afb1f18640632c10 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb4359f3dc8190a2330cf6efb8c084 |
completed | March 31, 2026, 3:45 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc944d009c81908ceb37b6922efb59 |
completed | April 1, 2026, 3:43 a.m. |
Created at: March 30, 2026, 5:33 p.m.