Triple
T4795450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Big Trail |
E106699
|
entity |
| Predicate | editedBy |
P1954
|
FINISHED |
| Object | Jack Dennis |
E224493
|
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: Jack Dennis | Statement: [The Big Trail, editedBy, Jack Dennis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Dennis Context triple: [The Big Trail, editedBy, Jack Dennis]
-
A.
Jack Dennis
chosen
Jack Dennis is an editor known for his work on the publication "Second Chorus."
-
B.
Max Dennison
Max Dennison is the skeptical teenage protagonist of the Halloween-themed fantasy film "Hocus Pocus," whose actions accidentally resurrect three witches in Salem.
-
C.
Dennis Awtrey
Dennis Awtrey is a former American professional basketball center known for his defensive play and role as a key contributor on several NBA teams during the 1970s and early 1980s.
-
D.
Henry Dutton
Henry Dutton was a 19th-century American lawyer, politician, and educator who served as governor of Connecticut and played a key role in the early development of legal education at Yale.
-
E.
Denis Barnett
Denis Barnett was a senior Royal Air Force officer who rose to high command during and after the Second World War.
- 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_69bd43f591c881909e5a532388b0f3f3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6609e9888190b49f99bb9fb2279d |
completed | March 20, 2026, 3:21 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69be43f512e0819086cc33009cd45c9a |
completed | March 21, 2026, 7:08 a.m. |
Created at: March 20, 2026, 1:22 p.m.