Triple
T13331559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | A56 |
E317585
|
entity |
| Predicate | startPoint |
P389
|
FINISHED |
| Object | Chester |
E640331
|
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: Chester | Statement: [A56, startPoint, Chester]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Chester Context triple: [A56, startPoint, Chester]
-
A.
Chester
Chester is the given name of Chester W. Nimitz, the prominent U.S. Navy fleet admiral who played a leading role in the Pacific theater during World War II.
-
B.
Chester
chosen
Chester is a historic walled city in northwest England renowned for its Roman heritage, medieval architecture, and well-preserved city walls.
-
C.
Chester
Chester is a historic walled city in northwest England, renowned for its well-preserved Roman and medieval architecture.
-
D.
Chester
Chester is a historic city in northwest England known for its Roman walls, medieval architecture, and distinctive black-and-white timbered buildings.
-
E.
Chester
Chester is the pet of Jonathan Byers, a character from the television series "Stranger Things."
- 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_69d806b4d62c81908d4ced1665414be5 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d9992fffa0819086610ae3bed2e2f9 |
completed | April 11, 2026, 12:43 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f71f329e148190a7741344b27ea663 |
completed | May 3, 2026, 10:10 a.m. |
Created at: April 9, 2026, 9:30 p.m.