Triple
T2768669
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mike Sullivan |
E61398
|
entity |
| Predicate | coachedTeamToTitle |
P24181
|
FINISHED |
| Object | Pittsburgh Penguins Stanley Cup championship |
—
|
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: Pittsburgh Penguins Stanley Cup championship | Statement: [Mike Sullivan, coachedTeamToTitle, Pittsburgh Penguins Stanley Cup championship]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: coachedTeamToTitle Context triple: [Mike Sullivan, coachedTeamToTitle, Pittsburgh Penguins Stanley Cup championship]
-
A.
teamManagedToTitle
Indicates that a team successfully achieved or secured a championship or title.
-
B.
coachingTeam
chosen
Indicates that one entity serves as a coach or coaching staff for a particular team.
-
C.
teamName
Indicates the relationship that assigns or associates a specific name with a particular team.
-
D.
teamTypeCoached
Indicates the type or category of team that an individual has coached.
-
E.
team2ConferenceTitles
Indicates the number of conference championship titles that the second team has won.
- 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_69ab4b7cd13481909174bca9809ed259 |
completed | March 6, 2026, 9:47 p.m. |
| NER | Named-entity recognition | batch_69abddceb9d88190961e30d521a21552 |
completed | March 7, 2026, 8:11 a.m. |
| PD | Predicate disambiguation | batch_69abdcfed608819080988e93df7bdf7c |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 9:57 p.m.