Triple
T780547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Midwest Region |
E16485
|
entity |
| Predicate | includesRounds |
P15100
|
FINISHED |
| Object | first round |
—
|
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: first round | Statement: [Midwest Region, includesRounds, first round]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: includesRounds Context triple: [Midwest Region, includesRounds, first round]
-
A.
hasProperRounds
Indicates that an entity is associated with rounds that meet specified standards or criteria for being considered proper or valid.
-
B.
hasRound
chosen
Indicates that an entity possesses, includes, or is associated with a particular round (e.g., a round of an event, game, or process).
-
C.
roundCount
Indicates the number of discrete rounds or iterations that have occurred or are allocated within a process, event, or interaction.
-
D.
hasPreliminaryRounds
Indicates that an event, competition, or process includes one or more initial qualifying rounds before the main or final stage.
-
E.
hasQualifyingRounds
Indicates that an event or competition includes preliminary qualifying rounds that participants must complete before advancing further.
- 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.