Triple
T8052826
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkmar High School |
E187715
|
entity |
| Predicate | city |
P40
|
FINISHED |
| Object | Lilburn |
E390857
|
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: Lilburn | Statement: [Berkmar High School, city, Lilburn]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Lilburn Context triple: [Berkmar High School, city, Lilburn]
-
A.
Lilburn, Georgia
chosen
Lilburn, Georgia is a suburban city in the Atlanta metropolitan area known for its diverse community and family-oriented neighborhoods.
-
B.
Marietta
Marietta is a feminine given name, often considered a diminutive or variant of names like Maria or Marita, used in various European and English-speaking cultures.
-
C.
Cedartown
Cedartown is a small city in northwestern Georgia known historically for its location within the mineral-rich Georgia Gold Belt and its role as a local industrial and railroad hub.
-
D.
Dawsonville
Dawsonville is a small city in north Georgia known for its gold rush history and strong ties to stock car racing and NASCAR culture.
-
E.
Loganville
Loganville is a suburban city in the Atlanta metropolitan area known for its residential communities and small-town character.
- 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_69ca82b15e948190a62fd7af5218426a |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3f7c425c8190aa1b2f534afeb58c |
completed | March 31, 2026, 3:29 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc572058048190996fa77774bf44ba |
completed | March 31, 2026, 11:22 p.m. |
Created at: March 30, 2026, 5:25 p.m.