Triple
T294770
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dallas Cowboys–Philadelphia Eagles rivalry |
E6068
|
entity |
| Predicate | fanCultureFeature |
P6226
|
FINISHED |
| Object | tailgating traditions |
—
|
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: tailgating traditions | Statement: [Dallas Cowboys–Philadelphia Eagles rivalry, fanCultureFeature, tailgating traditions]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fanCultureFeature Context triple: [Dallas Cowboys–Philadelphia Eagles rivalry, fanCultureFeature, tailgating traditions]
-
A.
fandomFocus
Indicates that one entity is primarily centered on, dedicated to, or concerned with the fan community or fan-related aspects of another entity.
-
B.
notableCultImage
Indicates that an entity is associated with a significant or historically important religious or cultic image.
-
C.
genreFeatures
Indicates that a particular genre is characterized or defined by certain features or attributes.
-
D.
fanbaseCharacteristic
chosen
Indicates a characteristic, trait, or common quality that typically describes or distinguishes the fanbase of an entity.
-
E.
film
Indicates that an entity is a movie or cinematic work, or that a relationship involves such a movie.
- 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_69a2e79114b081909490b3bf5a5dbb51 |
completed | Feb. 28, 2026, 1:03 p.m. |
| NER | Named-entity recognition | batch_69a2e9e273f88190ac5355d1310376ed |
completed | Feb. 28, 2026, 1:13 p.m. |
| PD | Predicate disambiguation | batch_69a2e9368894819093eeae4347dfcc5a |
completed | Feb. 28, 2026, 1:10 p.m. |
Created at: Feb. 28, 2026, 1:06 p.m.