Triple
T222486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hudson River Derby |
E4245
|
entity |
| Predicate | rivalryCharacterization |
P8314
|
FINISHED |
| Object | fiercely contested |
—
|
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: fiercely contested | Statement: [Hudson River Derby, rivalryCharacterization, fiercely contested]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: rivalryCharacterization Context triple: [Hudson River Derby, rivalryCharacterization, fiercely contested]
-
A.
rivalryName
Indicates that a specific name or label is assigned to a rivalry relationship between two entities.
-
B.
divisionRivalry
Indicates a competitive or adversarial relationship between entities that belong to the same division or subgroup within a larger organization or system.
-
C.
hasRivalryEmotion
Indicates that one entity feels rivalry-based emotions, such as competitive tension or antagonistic comparison, toward another entity.
-
D.
rivalLeague
Indicates that two leagues are in competition with each other, typically vying for similar audiences, resources, or status.
-
E.
foundedAsRivalOf
Indicates that an entity was established specifically to compete with or challenge another entity.
- 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_69a2573508588190b522c2476d91acfe |
completed | Feb. 28, 2026, 2:47 a.m. |
| NER | Named-entity recognition | batch_69a25c705fd88190bfee7f5e1f7cee17 |
completed | Feb. 28, 2026, 3:09 a.m. |
| PD | Predicate disambiguation | batch_69a25b5617788190814358aee3f7ae37 |
completed | Feb. 28, 2026, 3:04 a.m. |
| PDg | Predicate description generation | batch_69a25c2bda788190bcfc0bc94686f9e0 |
completed | Feb. 28, 2026, 3:08 a.m. |
Created at: Feb. 28, 2026, 2:53 a.m.