Triple
T22187505
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rome Derby |
E548332
|
entity |
| Predicate | hasRivalryCategory |
P146762
|
FINISHED |
| Object | Italian football derbies |
—
|
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: Italian football derbies | Statement: [Rome Derby, hasRivalryCategory, Italian football derbies]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRivalryCategory Context triple: [Rome Derby, hasRivalryCategory, Italian football derbies]
-
A.
hasRivalryAspect
Indicates that there exists a competitive or adversarial relationship or dimension between entities.
-
B.
hasRivalryContext
Indicates that there exists a competitive or adversarial relationship between entities within a specific situational or contextual framework.
-
C.
hasRivalryRoot
Indicates that a rivalry relationship originates from, or is fundamentally based on, a particular source, cause, or underlying factor.
-
D.
hasRivalrySport
Indicates a competitive relationship in which two entities are rivals specifically within the context of a sport or sporting activity.
-
E.
hasRivalryFormat
Indicates that there is a specific structure, set of rules, or format that defines how a rivalry between entities is conducted or organized.
- 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_69e11e3e0c7c8190b30d278845e2497e |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12aaa32288190830f6dfc626fb26a |
completed | April 28, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69e71b48576c8190a8e93738fd9cfda5 |
completed | April 21, 2026, 6:38 a.m. |
| PDg | Predicate description generation | batch_69e7222e74248190a2d3671049f117f2 |
completed | April 21, 2026, 7:07 a.m. |
Created at: April 16, 2026, 8:35 p.m.