Triple
T31674488
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 2005 MLS SuperDraft |
E808360
|
entity |
| Predicate | numberOfTeamsParticipating |
P6986
|
FINISHED |
| Object | 12 |
—
|
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: 12 | Statement: [2005 MLS SuperDraft, numberOfTeamsParticipating, 12]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTeamsParticipating Context triple: [2005 MLS SuperDraft, numberOfTeamsParticipating, 12]
-
A.
hasNumberOfTeams
chosen
Indicates the quantity of teams associated with or contained by a given entity.
-
B.
qualifiedTeamsCount
Indicates the number of teams that have successfully met the criteria to qualify for a given stage, event, or competition.
-
C.
numberOfTeamsVariesBetween
Indicates that the count of teams involved changes within a specified range or across different instances or conditions.
-
D.
numberOfParticipatingTeamsInQualifying
Indicates the total number of teams that take part in the qualifying stage of a competition or event.
-
E.
numberOfTeamsLater
Indicates that one entity has a greater number of teams than another entity at a later point in time.
- 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_69f348dcf5d48190ac25b1365ae717a8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a012efebda88190a90c8f650e4b1ee9 |
completed | May 11, 2026, 1:21 a.m. |
| PD | Predicate disambiguation | batch_6a01298cc604819087c836659c128926 |
completed | May 11, 2026, 12:57 a.m. |
Created at: April 30, 2026, 11:02 p.m.