Triple
T23504010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Honda-Broderick Cup |
E572231
|
entity |
| Predicate | sportingDomain |
P152628
|
FINISHED |
| Object | NCAA sports |
—
|
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: NCAA sports | Statement: [Honda-Broderick Cup, sportingDomain, NCAA sports]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: sportingDomain Context triple: [Honda-Broderick Cup, sportingDomain, NCAA sports]
-
A.
sportCreated
Indicates that an entity is the originator or inventor of a particular sport.
-
B.
sportsCategory
Indicates that one entity is classified as a type or category within the domain of sports to which the other entity belongs.
-
C.
sportFocus
Indicates that one entity has a primary emphasis, specialization, or concentration on a particular sport represented by the other entity.
-
D.
sportsModel
Indicates a relationship where an entity is a sports-oriented model or variant of another entity (such as a product, design, or system) optimized or styled for sporting use.
-
E.
sportCategory
Indicates that one entity is classified as a type or category of sport to which the other entity (typically a specific sport or sporting event) belongs.
- 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_69e245b5e4208190bac8a6509867e394 |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1a8fedbec8190b183661edaba4cd4 |
completed | April 29, 2026, 6:45 a.m. |
| PD | Predicate disambiguation | batch_69f0621165c08190a0b27b1319733959 |
completed | April 28, 2026, 7:30 a.m. |
| PDg | Predicate description generation | batch_69f0bd4a0e408190ad8916faf23562d9 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 17, 2026, 6:06 p.m.