Triple
T8299443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Acadia Axemen |
E194310
|
entity |
| Predicate | homeVenue |
P105
|
FINISHED |
| Object | Raymond Field |
E211369
|
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: Raymond Field | Statement: [Acadia Axemen, homeVenue, Raymond Field]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Raymond Field Context triple: [Acadia Axemen, homeVenue, Raymond Field]
-
A.
Raymond Field
chosen
Raymond Field is the main outdoor sports stadium at Acadia University, used primarily for football and other athletic events.
-
B.
Raymond Wheeler
Raymond Wheeler was a senior United States Army general who played a key leadership role in Allied operations in the China-Burma-India theater during World War II.
-
C.
Raymond Mansfield
Raymond Mansfield is a film producer best known for his work on acclaimed movies such as "BlacKkKlansman."
-
D.
Leo Farley
Leo Farley is a central character in the crime drama series "Under Suspicion," involved in the show's intricate investigations and moral ambiguities.
-
E.
Raymond Smith
Raymond Smith is a character known for being linked to the medical condition of dry eye.
- 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_69ca82e50ebc81909aa7b260c76bd757 |
completed | March 30, 2026, 2:04 p.m. |
| NER | Named-entity recognition | batch_69cb7dfb60e48190bfa5de1c1496d3b5 |
completed | March 31, 2026, 7:55 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cd68b6ad30819090d34d8e79cee634 |
completed | April 1, 2026, 6:49 p.m. |
Created at: March 30, 2026, 5:53 p.m.