Triple
T31783493
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English First Division 1968–69 |
E811266
|
entity |
| Predicate | fewestLossesNumber |
P172908
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [English First Division 1968–69, fewestLossesNumber, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fewestLossesNumber Context triple: [English First Division 1968–69, fewestLossesNumber, 2]
-
A.
fewestLossesTeam
Indicates that the referenced team is the one with the smallest number of losses compared to all other teams in the relevant set or competition.
-
B.
fewestGoalsTeam
Indicates the team that has conceded or scored the lowest number of goals compared to all other teams in the relevant context.
-
C.
fewestGoalsConcededRecordScope
Indicates the specific context or scope (such as competition, season, or time period) within which a record for the fewest goals conceded is defined.
-
D.
mostGamesLostBy
Indicates that one entity holds the record for having lost the greatest number of games to another entity.
-
E.
mostLossesTeam
Indicates the team that has incurred the greatest number of losses within a given set of teams or season.
- 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_69f348e544a48190ab6e700b05f6438c |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b0d21dd08190a9883ff71c94c71c |
completed | May 3, 2026, 2:20 a.m. |
| PD | Predicate disambiguation | batch_69f6aca3dedc81908b519d53d2909868 |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6afeaaef88190aefa97e83f8db906 |
completed | May 3, 2026, 2:16 a.m. |
Created at: April 30, 2026, 11:37 p.m.