Triple
T9302627
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | English First Division 1952–53 |
E223802
|
entity |
| Predicate | championsPoints |
P7114
|
FINISHED |
| Object | 54 |
—
|
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: 54 | Statement: [English First Division 1952–53, championsPoints, 54]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: championsPoints Context triple: [English First Division 1952–53, championsPoints, 54]
-
A.
totalPointsByChampionInFinal
Indicates the total number of points scored by a given champion in the final match or round.
-
B.
championRegularSeasonWins
Indicates that an entity is the champion based on having the highest number of regular season wins.
-
C.
winnerPoints
chosen
Indicates the number of points earned by the winning participant or entity in a competition or event.
-
D.
pointsLeader
Indicates that the subject entity is the current leader in points relative to other entities in a given context or competition.
-
E.
topScorerPoints
Indicates the number of points scored by the top-scoring entity in a given context or event.
- 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_69ca8424d0f08190831e2e93c6533aeb |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd08d34c4c819095a213360747c3a6 |
completed | April 1, 2026, noon |
| PD | Predicate disambiguation | batch_69cc7a5ef1908190bc5ca166bb895af6 |
completed | April 1, 2026, 1:52 a.m. |
Created at: March 30, 2026, 7:36 p.m.