Triple
T4536202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Erik Karlsson |
E107413
|
entity |
| Predicate | scored100PointSeason |
P57336
|
FINISHED |
| Object | 2022-2023 |
—
|
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: 2022-2023 | Statement: [Erik Karlsson, scored100PointSeason, 2022-2023]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: scored100PointSeason Context triple: [Erik Karlsson, scored100PointSeason, 2022-2023]
-
A.
scored100PointsInAGame
Indicates that an entity achieved a total of 100 points in a single game or match.
-
B.
winsInSingleSeason
Indicates that one entity achieves a specified number of wins within a single competitive season.
-
C.
teamIn100PointGame
Indicates that a team participated in a game in which at least one team scored 100 or more points.
-
D.
scoredFor
Indicates that one entity achieved points or a score on behalf of another entity, such as a player scoring for a team.
-
E.
scoredOverPointsCareer
Indicates that an entity (typically an athlete) accumulated more than a specified number of points over the course of their entire career.
- 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_69bd43f922788190b7edfa294e39b178 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd57b634b08190845d04213cf8d5b9 |
completed | March 20, 2026, 2:20 p.m. |
| PD | Predicate disambiguation | batch_69bd521edd00819099dfccaa65dddd61 |
completed | March 20, 2026, 1:56 p.m. |
| PDg | Predicate description generation | batch_69bd56b3e4c88190a7ade3d0ed0ab606 |
completed | March 20, 2026, 2:16 p.m. |
Created at: March 20, 2026, 1:04 p.m.