Triple
T13665180
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Killington Resort |
E327097
|
entity |
| Predicate | WorldCupVenueSince |
P111057
|
FINISHED |
| Object | 2016 |
—
|
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: 2016 | Statement: [Killington Resort, WorldCupVenueSince, 2016]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: WorldCupVenueSince Context triple: [Killington Resort, WorldCupVenueSince, 2016]
-
A.
associatedWithCountryStadium
Indicates that there is an association or connection between a country and a stadium, such as location, ownership, or primary use.
-
B.
FIFAStadiumCategory
Indicates the classification level or category assigned to a stadium according to FIFA’s official stadium standards and requirements.
-
C.
associatedStadiums
Indicates that there is a relationship linking an entity to one or more stadiums with which it is connected or affiliated.
-
D.
stadiumUsedFor
Indicates that a particular stadium is used for a specific activity, event, or purpose.
-
E.
worldCupHostYear
Indicates the year in which a particular country or location served as the host of the FIFA World Cup tournament.
- 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_69d8076d8270819092afc2f0e9c359a8 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dbc623fcc88190bbad97541c040b7a |
completed | April 12, 2026, 4:19 p.m. |
| PD | Predicate disambiguation | batch_69dbbe8d8d0881908d6e89954f44eed4 |
completed | April 12, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69dbc59ca1a88190a6abd3bd00554c93 |
completed | April 12, 2026, 4:17 p.m. |
Created at: April 9, 2026, 9:52 p.m.