Triple
T11151289
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Liberty Bell Classic |
E263790
|
entity |
| Predicate | medalEventsCountApprox |
P80583
|
FINISHED |
| Object | 30 |
—
|
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: 30 | Statement: [Liberty Bell Classic, medalEventsCountApprox, 30]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: medalEventsCountApprox Context triple: [Liberty Bell Classic, medalEventsCountApprox, 30]
-
A.
numberOfMedalEvents
chosen
Indicates the total count of distinct medal-awarding events associated with a given context (such as a sport, competition, or edition of games).
-
B.
medalEventsFor
Indicates a relationship where one entity lists or specifies the medal-awarding events associated with another entity.
-
C.
hasMedalEvents
Indicates that an entity has associated events in which medals are or can be awarded.
-
D.
hasMedalCount
Indicates the relationship between an entity and the number of medals it possesses or has been awarded.
-
E.
OlympicMedalEvent
Indicates that an entity represents a specific Olympic Games event in which medals are awarded.
- 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_69d6aa9ccddc8190868998c8b7beb060 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8719e74819095413abc6c79296c |
completed | April 9, 2026, 5:57 p.m. |
| PD | Predicate disambiguation | batch_69d75ce71944819089eee9b5c9283cbd |
completed | April 9, 2026, 8:01 a.m. |
Created at: April 8, 2026, 9:28 p.m.