Triple
T7994940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chicago Bears Ring of Honor |
E186100
|
entity |
| Predicate | associatedFranchiseFounded |
P46462
|
FINISHED |
| Object | 1920 |
—
|
LITERAL 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: 1920 | Statement: [Chicago Bears Ring of Honor, associatedFranchiseFounded, 1920]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedFranchiseFounded Context triple: [Chicago Bears Ring of Honor, associatedFranchiseFounded, 1920]
-
A.
foundedFranchise
Indicates that an entity established or created a particular franchise.
-
B.
foundedAsFranchiseYear
chosen
Indicates the year in which an entity was established specifically as a franchise.
-
C.
appliedToFranchiseFoundedIn
Indicates that something (such as a rule, policy, or action) is applied specifically to a franchise that was founded in a particular time or place.
-
D.
associatedFranchise
Indicates a relationship where one entity is linked to, or belongs within, a particular franchise or franchise universe.
-
E.
historicalFranchiseOf
Indicates that one entity is or was a franchise (such as a team, branch, or licensed operation) that historically belonged to or operated under another entity.
- F. None of above.
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_69ca829c6c308190ab05b43d234c52b2 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb3c7547dc8190a60a06b3d61764b0 |
completed | March 31, 2026, 3:16 a.m. |
| PD | Predicate disambiguation | batch_69cb0483d3b48190b250c7603d747bca |
completed | March 30, 2026, 11:17 p.m. |
Created at: March 30, 2026, 5:17 p.m.