Triple
T4758685
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | World Games |
E105648
|
entity |
| Predicate | usesMedalTable |
P58340
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [World Games, usesMedalTable, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesMedalTable Context triple: [World Games, usesMedalTable, yes]
-
A.
hasMedalCount
Indicates the relationship between an entity and the number of medals it possesses or has been awarded.
-
B.
includesMedal
Indicates that an entity’s set, collection, or record contains or features a particular medal as one of its elements.
-
C.
thirdInMedalTable
Indicates that an entity finished in third place in a ranking of medal counts (a medal table), typically in a competition or multi-sport event.
-
D.
medalTableLeader
Indicates that an entity is currently leading the medal table, typically having the highest overall medal standing compared to others.
-
E.
wonMedalAt
Indicates that an entity received a medal as a result of participating in a specific event or competition.
- 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_69bd43f14cac819081c7c69803648211 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd650c11f4819098cd1f490f711dc8 |
completed | March 20, 2026, 3:17 p.m. |
| PD | Predicate disambiguation | batch_69bd6225c9488190afee5bb3619d0365 |
completed | March 20, 2026, 3:05 p.m. |
| PDg | Predicate description generation | batch_69bd631328fc81909b28ae0a2a3ed9bb |
completed | March 20, 2026, 3:09 p.m. |
Created at: March 20, 2026, 1:20 p.m.