Triple
T5586008
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ripon Middle School |
E146758
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Ripon |
E128918
|
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: Ripon | Statement: [Ripon Middle School, city, Ripon]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ripon Context triple: [Ripon Middle School, city, Ripon]
-
A.
Ripon
chosen
Ripon is a small city in California’s Central Valley known for its agricultural roots and tight-knit community.
-
B.
Ripon
Ripon is a historic cathedral city in North Yorkshire, England, known for Ripon Cathedral and its traditional hornblower ceremony.
-
C.
City of York
The City of York is a historic cathedral city in North Yorkshire, England, renowned for its medieval walls, Gothic York Minster, and well-preserved old town.
-
D.
Chester
Chester is a small, historically industrial city in southeastern Pennsylvania that lies just southwest of Philadelphia along the Delaware River.
-
E.
Chester
Chester is the full given name of American actor and musician Chet Hanks, son of actor Tom Hanks.
- 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_69c0090287a08190b4098411effe970c |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020871a3c8190991f291295cadfa5 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c07d8c6f8881909ac2018d11f5aef8 |
completed | March 22, 2026, 11:38 p.m. |
Created at: March 22, 2026, 3:38 p.m.