Triple
T347389
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas Cowboys–New York Giants rivalry |
E6970
|
entity |
| Predicate | typicalNumberOfMeetingsPerSeason |
P12655
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [Dallas Cowboys–New York Giants rivalry, typicalNumberOfMeetingsPerSeason, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalNumberOfMeetingsPerSeason Context triple: [Dallas Cowboys–New York Giants rivalry, typicalNumberOfMeetingsPerSeason, 2]
-
A.
typicalSeasonMeetings
Indicates that there are regularly occurring meetings associated with a particular season or time period.
-
B.
totalMatchesPerSeason
Indicates the total number of matches associated with an entity within a single season.
-
C.
typicalMeetingMonth
Indicates the month in which an entity most commonly or usually holds its meetings.
-
D.
seasonStructure
Indicates how a season is organized or structured in terms of its component parts, phases, or format.
-
E.
meetsEvery
Indicates that one entity encounters or comes into contact with every member of a specified set of entities.
- 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_69a2e7951ba08190960e90823b5078f3 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2eb1a37c08190b1380f6bf8513a37 |
completed | Feb. 28, 2026, 1:18 p.m. |
| PD | Predicate disambiguation | batch_69a2e95451a4819090f4e4fb9b21a493 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eae0bd7081908197bbf5c55fe647 |
completed | Feb. 28, 2026, 1:17 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.