Triple
T20171681
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montenegro at the Summer Olympics |
E491974
|
entity |
| Predicate | hasMedalInYear |
P102988
|
FINISHED |
| Object | 2012 |
—
|
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: 2012 | Statement: [Montenegro at the Summer Olympics, hasMedalInYear, 2012]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMedalInYear Context triple: [Montenegro at the Summer Olympics, hasMedalInYear, 2012]
-
A.
hasMultipleMedalsPerYear
Indicates that an entity has been awarded more than one medal within the same calendar year.
-
B.
yearOfMedal
chosen
Indicates the specific year in which a particular medal was awarded or received.
-
C.
hasMedalEquivalent
Indicates that one medal is considered equivalent in value, status, or recognition to another medal.
-
D.
hasMedalComponent
Indicates that something includes or is composed of a particular medal or medal-related part as one of its components.
-
E.
hasMedalCount
Indicates the relationship between an entity and the number of medals it possesses or has been 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66848ae3c8190aa5fde66da35a89a |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:35 p.m.