Triple
T10838186
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tyreek Hill |
E255814
|
entity |
| Predicate | teamNumberWithKansasCityChiefs |
P95988
|
FINISHED |
| Object | 10 |
—
|
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: 10 | Statement: [Tyreek Hill, teamNumberWithKansasCityChiefs, 10]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: teamNumberWithKansasCityChiefs Context triple: [Tyreek Hill, teamNumberWithKansasCityChiefs, 10]
-
A.
proBowlTeam
Indicates that a player was selected to and participated on a specific team in the Pro Bowl all-star game.
-
B.
NFLTeam
Indicates a relationship where an entity is identified as a professional American football team that competes in the National Football League.
-
C.
cbaTeam
Indicates that one entity is a member of, or associated with, a specific CBA (Collective Bargaining Agreement) team.
-
D.
superBowlTeam
Indicates that a team participated as one of the competing teams in a specific Super Bowl game.
-
E.
leagueTeam2
Indicates that the subject entity is the second team participating in a particular league, matchup, or league-related context.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d747002b3081908726901ee83d8f38 |
completed | April 9, 2026, 6:28 a.m. |
| PD | Predicate disambiguation | batch_69d70d25280c8190b648d7d1958b413a |
completed | April 9, 2026, 2:21 a.m. |
| PDg | Predicate description generation | batch_69d7101c96708190808fef73199e8482 |
completed | April 9, 2026, 2:34 a.m. |
Created at: April 8, 2026, 9:19 p.m.