Triple
T797934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkshire County |
E17062
|
entity |
| Predicate | containsTown |
P847
|
FINISHED |
| Object | Lee |
E762
|
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: Lee | Statement: [Berkshire County, containsTown, Lee]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lee Context triple: [Berkshire County, containsTown, Lee]
-
A.
Lee
chosen
Lee is a given name shared by numerous individuals across different cultures and professions.
-
B.
Lou
Lou is a common diminutive form of the given name Louise.
-
C.
Larry
Larry is the given name of Larry Bird, the legendary Hall of Fame Boston Celtics forward widely regarded as one of the greatest basketball players in NBA history.
-
D.
Lewis
"Lewis" is a notable film or television work featuring British actor Edward Fox, recognized as part of his distinguished acting career.
-
E.
Neil
Neil is the given name of Neil deGrasse Tyson, a prominent American astrophysicist, author, and science communicator.
- 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_69a49378b9c48190adbf5f62e5b7aca1 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a7b342888190a344fe81a2c9f33c |
completed | March 1, 2026, 8:55 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69a76d7fba6c819097d8e2d962d0241f |
completed | March 3, 2026, 11:23 p.m. |
Created at: March 1, 2026, 7:38 p.m.