Triple
T7800401
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cambridge University Boat Club |
E180414
|
entity |
| Predicate | raceFrequency |
P37986
|
FINISHED |
| Object | annual |
—
|
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: annual | Statement: [Cambridge University Boat Club, raceFrequency, annual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: raceFrequency Context triple: [Cambridge University Boat Club, raceFrequency, annual]
-
A.
raceRole
Indicates the specific role, position, or function an entity holds within a race or racing event.
-
B.
racialComposition
Indicates the proportional makeup of different racial groups within a given population or entity.
-
C.
relatedRace
Indicates that there is a connection or association between two races, such as similarity, relevance, or contextual linkage.
-
D.
frequencyOfCensus
Indicates how often a census is conducted or occurs within a given context or jurisdiction.
-
E.
frequencyCategory
chosen
Indicates how often an action, event, or relationship occurs, typically by assigning it to a qualitative frequency level (e.g., rare, occasional, frequent).
- 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_69ca827e50cc8190a92a733577184938 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69caf78a6d88819093f83528fe88b182 |
completed | March 30, 2026, 10:22 p.m. |
| PD | Predicate disambiguation | batch_69cae9111b2481909684a2d4aa4831c2 |
completed | March 30, 2026, 9:20 p.m. |
Created at: March 30, 2026, 4:33 p.m.