Triple
T9683245
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bernie Federko |
E234338
|
entity |
| Predicate | teamSpecialRecognition |
P89608
|
FINISHED |
| Object | St. Louis Blues retired number 24 |
—
|
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: St. Louis Blues retired number 24 | Statement: [Bernie Federko, teamSpecialRecognition, St. Louis Blues retired number 24]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamSpecialRecognition Context triple: [Bernie Federko, teamSpecialRecognition, St. Louis Blues retired number 24]
-
A.
teamHonors
Indicates that a team has received a particular honor, award, or title.
-
B.
teamHonor
Indicates that an honor, award, or recognition is attributed to or received by a team.
-
C.
teamSpecialty
Indicates the particular area of expertise or focus that characterizes a team’s skills or activities.
-
D.
teamHonour
Indicates that a team has received or been awarded a particular honour, title, or distinction.
-
E.
teamHonourWith
Indicates that a team has been awarded or recognized with a particular honour or distinction.
- F. None of above. chosen
Provenance (4 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_69ca84c99e34819092e5563a7106cfca |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9ccdbcc48190a4a9a70b3f419ac2 |
completed | April 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
| PDg | Predicate description generation | batch_69ccd9408c848190b84dd74d87f76273 |
completed | April 1, 2026, 8:37 a.m. |
Created at: March 30, 2026, 8:16 p.m.