Triple
T11876336
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Blunder Bowl |
E282535
|
entity |
| Predicate | associatedWithTurnoversTotal |
P41443
|
FINISHED |
| Object | 11 |
—
|
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: 11 | Statement: [Blunder Bowl, associatedWithTurnoversTotal, 11]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedWithTurnoversTotal Context triple: [Blunder Bowl, associatedWithTurnoversTotal, 11]
-
A.
turnoversTotal
chosen
Indicates the total number of times possession changes from one entity to another, typically due to errors, losses, or rule-based transfers.
-
B.
statRebounds
Indicates the number of rebounds an entity (typically a player or team) records in a game or over a specified period.
-
C.
coltsTurnovers
Indicates the number of times the Colts lost possession of the ball to the opposing team through turnovers (such as interceptions or fumbles).
-
D.
scoredAssists
Indicates that one entity contributed an assist that led to another entity scoring (typically in a game or sports context).
-
E.
cowboysTurnovers
Indicates the number of times the Cowboys lose possession of the ball to the opposing team through fumbles or interceptions.
- 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_69d6ab2945d081908a5851c916cbcfb5 |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8d39d2934819093b9f7006f45e5cb |
completed | April 10, 2026, 10:40 a.m. |
| PD | Predicate disambiguation | batch_69d8bb272f88819090c37c944c5a60ab |
completed | April 10, 2026, 8:56 a.m. |
Created at: April 8, 2026, 9:44 p.m.