Triple
T30682410
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Football League Championship 2013–14 with Leicester City F.C. |
E781089
|
entity |
| Predicate | pointsTotal |
P17024
|
FINISHED |
| Object | 102 |
—
|
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: 102 | Statement: [Football League Championship 2013–14 with Leicester City F.C., pointsTotal, 102]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: pointsTotal Context triple: [Football League Championship 2013–14 with Leicester City F.C., pointsTotal, 102]
-
A.
pointsAwarded
Indicates that a specified number of points has been granted to an entity as a result of some action or event.
-
B.
totalPointsAvailable
Indicates the complete number of points that can be obtained or assigned within a given context or activity.
-
C.
pointsForWin
Indicates the number of points awarded to an entity for achieving a win in a given context or competition.
-
D.
points
Indicates that one entity directs attention, focus, or a physical/abstract indication toward another entity or location.
-
E.
totalPointsScored
chosen
Indicates the total number of points accumulated or scored by an entity over a defined period, event, or context.
- 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_69f224a92f54819095499b4d32bd5134 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f68b81f12c8190a0aaacc0a54f9db5 |
completed | May 2, 2026, 11:40 p.m. |
| PD | Predicate disambiguation | batch_69f6861170d08190bb98be609d436f84 |
completed | May 2, 2026, 11:17 p.m. |
Created at: April 29, 2026, 8:33 p.m.