Triple
T13626657
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baltimore Colts offense |
E325599
|
entity |
| Predicate | knownForGame |
P5150
|
FINISHED |
| Object | 1958 NFL Championship Game |
—
|
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: 1958 NFL Championship Game | Statement: [Baltimore Colts offense, knownForGame, 1958 NFL Championship Game]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: knownForGame Context triple: [Baltimore Colts offense, knownForGame, 1958 NFL Championship Game]
-
A.
knownForStoryline
Indicates that an entity is recognized or notable specifically for its narrative or storyline.
-
B.
namedForKnownFor
Indicates that one entity is named after another entity specifically because that other entity is notable or recognized for something.
-
C.
knownForSports
chosen
Indicates that an entity is recognized or notable for its involvement, achievement, or association with sports.
-
D.
segmentKnownFor
Indicates that a specific segment or portion of something is recognized or notable for a particular characteristic, feature, or association.
-
E.
formerlyKnownFor
Indicates that an entity was previously recognized or notable for a particular role, attribute, or activity, but is no longer primarily associated with it.
- 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_69d8076aae28819092cf636190ee5529 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc60635d08190899806fe8936f02a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe85e1c4819095194f4b7f9f6118 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:51 p.m.