Triple
T2904180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Joseph Jackson Gibbs |
E62723
|
entity |
| Predicate | SuperBowlTitlesWonAsHeadCoach |
P7109
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [Joseph Jackson Gibbs, SuperBowlTitlesWonAsHeadCoach, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: SuperBowlTitlesWonAsHeadCoach Context triple: [Joseph Jackson Gibbs, SuperBowlTitlesWonAsHeadCoach, 3]
-
A.
SuperBowlTitlesAsHeadCoach
Indicates the number of Super Bowl titles an individual has won specifically in the role of head coach.
-
B.
numberOfSuperBowlsWonAsHeadCoach
chosen
Indicates the total count of Super Bowl championships an individual has won while serving in the role of head coach.
-
C.
wonSuperBowlAsHeadCoachWith
Indicates that one entity served as the head coach of a team that won the Super Bowl with the other entity (the team) during that championship season.
-
D.
SuperBowlAppearanceAsHeadCoach
Indicates that a person, in their role as a head coach, led a team that participated in a Super Bowl game.
-
E.
hasCoachedInSuperBowl
Indicates that a person has served as a coach in at least one Super Bowl game.
- 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_69ab4c3e070c8190b78d3d2c005876dd |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abe0b5546c8190852d9a454e41eee6 |
completed | March 7, 2026, 8:24 a.m. |
| PD | Predicate disambiguation | batch_69abdd19bac881908f047d616aca8438 |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:11 p.m.