Triple
T872449
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Bluest Eye |
E18843
|
entity |
| Predicate | settingPlace |
P1957
|
FINISHED |
| Object | Lorain, Ohio |
E20113
|
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: Lorain, Ohio | Statement: [The Bluest Eye, settingPlace, Lorain, Ohio]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lorain, Ohio Context triple: [The Bluest Eye, settingPlace, Lorain, Ohio]
-
A.
Lorain, Ohio, United States
chosen
Lorain, Ohio, United States is an industrial city on Lake Erie best known as the birthplace of Nobel Prize–winning author Toni Morrison.
-
B.
Youngstown
Youngstown is an industrial city in northeastern Ohio historically known for its steel production and central role in the Rust Belt’s economic rise and decline.
-
C.
Akron
Akron is an industrial city in northeastern Ohio known historically for its rubber and tire manufacturing industry.
-
D.
Norwalk, Ohio
Norwalk, Ohio is a small city in northern Ohio that serves as the county seat of Huron County and a regional hub for the surrounding rural communities.
-
E.
Cleveland
Cleveland is a common English surname most prominently associated with Grover Cleveland, the 22nd and 24th president of the United States.
- 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_69a4938db1f081909bcd1ad2713b6096 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4ac96850881908a2d776685126137 |
completed | March 1, 2026, 9:16 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ac660a86d881908ae96a5492c9b9a2 |
completed | March 7, 2026, 5:53 p.m. |
Created at: March 1, 2026, 7:39 p.m.