Triple
T319259
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia Eagles–New York Giants rivalry |
E7775
|
entity |
| Predicate | matchupFrequency |
P12965
|
FINISHED |
| Object | twice per regular season |
—
|
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: twice per regular season | Statement: [Philadelphia Eagles–New York Giants rivalry, matchupFrequency, twice per regular season]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchupFrequency Context triple: [Philadelphia Eagles–New York Giants rivalry, matchupFrequency, twice per regular season]
-
A.
hasRivalryAspect
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
B.
isDivisionalMatchup
Indicates that the two entities (typically teams) are competing against each other within the same division.
-
C.
frequentlyTradedAgainst
Indicates that two entities are commonly exchanged or traded with each other in a significant number of transactions over time.
-
D.
matches
Indicates that two entities correspond to or are in agreement with each other according to some defined criteria or pattern.
-
E.
matchPointsDraw
Indicates that the entities receive or share an equal number of points as a result of a drawn or tied match.
- 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_69a2e7e7af7881908890039d6be4e9b8 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2eb7df63c8190b7cd1bcfdfd96187 |
completed | Feb. 28, 2026, 1:19 p.m. |
| PD | Predicate disambiguation | batch_69a2e94513ec819089f5177f7a521e65 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2eb7c56bc8190ab787801af2eec8d |
completed | Feb. 28, 2026, 1:19 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.