Triple
T24946567
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Melbourne Sports and Entertainment Precinct |
E624197
|
entity |
| Predicate | hasWorldClassVenues |
P165807
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Melbourne Sports and Entertainment Precinct, hasWorldClassVenues, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasWorldClassVenues Context triple: [Melbourne Sports and Entertainment Precinct, hasWorldClassVenues, yes]
-
A.
hasMajorVenue
Indicates that an entity is associated with a primary or principal venue where its main activities or events take place.
-
B.
hasProfessionalSportsVenue
Indicates that one entity possesses or hosts a venue specifically used for professional sports events.
-
C.
hasSportsVenueHistory
Indicates that there exists a historical relationship between an entity and a sports venue, such as past use, events held, or occupancy over time.
-
D.
isOneOfLargestVenuesIn
Indicates that an entity is among the largest venues located within a specified place or region.
-
E.
hasSportsVenueType
Indicates that a sports venue is classified as being of a specific type or category (e.g., stadium, arena, court).
- 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_69e2ff22e4c48190a0444b5a044f14e8 |
completed | April 18, 2026, 3:48 a.m. |
| NER | Named-entity recognition | batch_69f65b14512c8190a40e70319dcc54cd |
completed | May 2, 2026, 8:14 p.m. |
| PD | Predicate disambiguation | batch_69f659cc571c819097e51e531961d812 |
completed | May 2, 2026, 8:08 p.m. |
| PDg | Predicate description generation | batch_69f65a9cb0bc8190bf8a9b319900bad5 |
completed | May 2, 2026, 8:12 p.m. |
Created at: April 18, 2026, 5:54 a.m.