Triple
T28860041
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Renegades |
E728833
|
entity |
| Predicate | hasRosterSizeType |
P89251
|
FINISHED |
| Object | American football 11-man rules |
—
|
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: American football 11-man rules | Statement: [Renegades, hasRosterSizeType, American football 11-man rules]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRosterSizeType Context triple: [Renegades, hasRosterSizeType, American football 11-man rules]
-
A.
hasRosterSizeCategory
chosen
Indicates the classification of an entity based on the size of its roster or group of members.
-
B.
hasRosterStatus
Indicates the current membership or availability status of an entity within a defined roster or lineup.
-
C.
rosterSize
Indicates the total number of individuals included on a given roster.
-
D.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
-
E.
hasTypicalMemberSize
Indicates the usual or characteristic size associated with members of a given class or group.
- 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_69f031a01cbc8190ba87270bb6fe4639 |
completed | April 28, 2026, 4:03 a.m. |
| NER | Named-entity recognition | batch_69f7979a073881909a4fde2558e6b6f3 |
completed | May 3, 2026, 6:44 p.m. |
| PD | Predicate disambiguation | batch_69f7961550f88190b7bb8a9155458b54 |
completed | May 3, 2026, 6:38 p.m. |
Created at: April 28, 2026, 6:46 a.m.