Triple
T11559031
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Birmingham Americans |
E274087
|
entity |
| Predicate | headCoach |
P256
|
FINISHED |
| Object | Jack Gotta |
E851979
|
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 Gotta | Statement: [Birmingham Americans, headCoach, Jack Gotta]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Jack Gotta Context triple: [Birmingham Americans, headCoach, Jack Gotta]
-
A.
Jack Gotta
chosen
Jack Gotta was a prominent Canadian Football League coach and executive best known for leading multiple teams to success in the 1970s and 1980s.
-
B.
Mic Jack
Mic Jack is a track by Big Boi featured on his 2017 studio album "Boomiverse."
-
C.
Jack
Jack is a common masculine given name, often used as a familiar form of John and widely featured in English-language literature and popular culture.
-
D.
Jack
Jack is the standard botanical author abbreviation for William Jack, a 19th-century Scottish physician and botanist known for his work on Southeast Asian flora.
-
E.
Jimmy Ba
Jimmy Ba is a prominent machine learning researcher known for his work on deep learning optimization methods such as the Adam optimizer.
- 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_69d6aae4dfa48190a3ab0b19a159a3c5 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88a888e8481909386009b9603e4d3 |
completed | April 10, 2026, 5:28 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e6e88b84d48190948243646bb5fd2b |
completed | April 21, 2026, 3:01 a.m. |
Created at: April 8, 2026, 9:37 p.m.