Triple
T24707735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2018–2019 Premier League |
E611942
|
entity |
| Predicate | secondMostPointsTeam |
P157817
|
FINISHED |
| Object | Liverpool F.C. |
—
|
NE NERFINISHED |
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: Liverpool F.C. | Statement: [2018–2019 Premier League, secondMostPointsTeam, Liverpool F.C.]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: secondMostPointsTeam Context triple: [2018–2019 Premier League, secondMostPointsTeam, Liverpool F.C.]
-
A.
secondFinishingTeam
Indicates that a team finished in second place in a competition or event.
-
B.
secondPlaceTeamRecord
Indicates the win-loss (and possibly tie) performance record of the team that finished in second place in a competition or league.
-
C.
stateTeam2
Indicates that a second team is associated with, represents, or belongs to a particular state or region.
-
D.
regionTeam2
Indicates that a second team or group is associated with, belongs to, or operates within a particular region.
-
E.
teamWithSecondMostTitles
Indicates that the subject is the team that has won the second-highest number of titles within a given competition or 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_69e2c4d9c24c8190a3712d74327f0c6e |
completed | April 17, 2026, 11:40 p.m. |
| NER | Named-entity recognition | batch_69f453035f508190be83a3d521723acf |
completed | May 1, 2026, 7:15 a.m. |
| PD | Predicate disambiguation | batch_69f44d6ef33081908f5d36ba1ae5f473 |
completed | May 1, 2026, 6:51 a.m. |
| PDg | Predicate description generation | batch_69f45300bd488190bb1d4160f5534ef6 |
completed | May 1, 2026, 7:15 a.m. |
Created at: April 18, 2026, 3:24 a.m.