Triple
T20409790
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avonmore |
E500557
|
entity |
| Predicate | hasTrack |
P3284
|
FINISHED |
| Object | Avonmore |
—
|
NE NERFINISHED |
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: Avonmore | Statement: [Avonmore, hasTrack, Avonmore]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Avonmore Context triple: [Avonmore, hasTrack, Avonmore]
-
A.
Avonmore
chosen
Avonmore is a small rural community located within Russell County in the Canadian province of Ontario.
-
B.
Moate
Moate is a small town in central Ireland known for its location on the old Dublin–Galway road and its surrounding agricultural countryside.
-
C.
Borrisoleigh
Borrisoleigh is a rural village in Ireland known for its strong hurling tradition and scenic location in the northern part of County Tipperary.
-
D.
Tinonee
Tinonee is a small rural village in New South Wales, Australia, known for its historic charm and riverside setting near Taree.
-
E.
Fourneaux
Fourneaux is a small French commune in the Savoie department of southeastern France, situated in the Alps near the Italian border.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0b4a935588190b9446a99b37ced44 |
completed | April 16, 2026, 10:06 a.m. |
| NER | Named-entity recognition | batch_69e67a3e0c1c8190be39d7f09c839dfa |
completed | April 20, 2026, 7:10 p.m. |
Created at: April 16, 2026, 11:29 a.m.