Triple
T7427251
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chinese Super League |
E171398
|
entity |
| Predicate | hasTransferWindow |
P76945
|
FINISHED |
| Object | winter transfer window |
—
|
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: winter transfer window | Statement: [Chinese Super League, hasTransferWindow, winter transfer window]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTransferWindow Context triple: [Chinese Super League, hasTransferWindow, winter transfer window]
-
A.
notableTransferWindow
Indicates that a transfer window (period for player transfers) is regarded as particularly significant or noteworthy in some context.
-
B.
canLoanPlayersTo
Indicates that one entity has the authority or ability to temporarily transfer its players to another entity.
-
C.
hasTransfer
Indicates a relationship where something is moved or conveyed from one entity or location to another.
-
D.
hasFreeTransfer
Indicates that one entity allows or provides a transfer to another service, route, or segment without additional cost.
-
E.
transferLine
Indicates a relationship where something is moved or conveyed from one point, medium, or entity to another along a defined path or channel.
- 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_69c68a63491881909281f73d4d5643bf |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f3055b7881908269ab909c5a85b5 |
completed | March 27, 2026, 9:13 p.m. |
| PD | Predicate disambiguation | batch_69c6f03648d08190b862d07fef71210c |
completed | March 27, 2026, 9:01 p.m. |
| PDg | Predicate description generation | batch_69c6f1ee5ab8819091082324f2dc3b8c |
completed | March 27, 2026, 9:09 p.m. |
Created at: March 27, 2026, 3:12 p.m.