Triple
T11374219
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tillicoultry |
E269422
|
entity |
| Predicate | near |
P350
|
FINISHED |
| Object | Alva |
E112949
|
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: Alva | Statement: [Tillicoultry, near, Alva]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Alva Context triple: [Tillicoultry, near, Alva]
-
A.
Alva
Alva is the middle name of the famed American inventor Thomas Edison, often used as part of his full name, Thomas Alva Edison.
-
B.
Alva
chosen
Alva is a small town in central Scotland situated at the foot of the Ochil Hills in Clackmannanshire.
-
C.
Alva
Alva is a small city in northwestern Oklahoma known as the county seat of Woods County and home to Northwestern Oklahoma State University.
-
D.
Alva
Alva is a small unincorporated community in Lee County, Florida, known for its historic rural character along the Caloosahatchee River.
-
E.
Dalva
Dalva is a surname most notably associated with American film editor Robert Dalva, recognized for his work on major Hollywood productions.
- 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_69d6aacca1048190b39dbbc2174616fa |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea8d244c8190b865260338edb532 |
completed | April 9, 2026, 6:06 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5568e3e108190ab843236b417f150 |
completed | April 19, 2026, 10:26 p.m. |
Created at: April 8, 2026, 9:33 p.m.