Triple
T780559
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midwest Region |
E16485
|
entity |
| Predicate | hasVenuePattern |
P10640
|
FINISHED |
| Object | games played at predetermined neutral sites |
—
|
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: games played at predetermined neutral sites | Statement: [Midwest Region, hasVenuePattern, games played at predetermined neutral sites]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVenuePattern Context triple: [Midwest Region, hasVenuePattern, games played at predetermined neutral sites]
-
A.
refersToVenueType
chosen
Indicates that one entity specifies or identifies the type or category of venue associated with another entity.
-
B.
usualVenueSince
Indicates that a particular venue has been the regular or customary location for something (e.g., an event or activity) starting from a specified point in time.
-
C.
servesVenue
Indicates that an entity provides services or functions in support of a particular venue.
-
D.
venue
Indicates the place or location where an event, activity, or interaction takes place.
-
E.
numberOfVenues
Indicates the total count of venues associated with a given entity 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_69a4936ad1fc81908f190208059ccf78 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a90365648190ace53b0f0e87aa68 |
completed | March 1, 2026, 9 p.m. |
| PD | Predicate disambiguation | batch_69a4a50bd23081908908235b8ec9201e |
completed | March 1, 2026, 8:43 p.m. |
Created at: March 1, 2026, 7:37 p.m.