Triple
T19955427
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Czech Olympic team |
E479668
|
entity |
| Predicate | firstSummerAppearanceAsCzechRepublic |
P118840
|
FINISHED |
| Object | 1996 Summer Olympics |
—
|
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: 1996 Summer Olympics | Statement: [Czech Olympic team, firstSummerAppearanceAsCzechRepublic, 1996 Summer Olympics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: firstSummerAppearanceAsCzechRepublic Context triple: [Czech Olympic team, firstSummerAppearanceAsCzechRepublic, 1996 Summer Olympics]
-
A.
CzechRepublicIsMemberOf
Indicates that the Czech Republic belongs to or holds membership in a specified organization, group, or alliance.
-
B.
timeUnderCzechoslovakia
Indicates that the subject entity existed or was in effect during the historical period when Czechoslovakia was a state.
-
C.
firstWinterAppearance
Indicates that the subject entity makes its first observed or recorded appearance during the winter season.
-
D.
firstInternationalAppearance
chosen
Indicates the event or time when an entity participates for the first time at an international level.
-
E.
numberOfGamesInCzechoslovakia
Indicates the total count of games that took place in Czechoslovakia.
- 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_69d8e523c19881909f9197037200dde6 |
completed | April 10, 2026, 11:55 a.m. |
| NER | Named-entity recognition | batch_69e65aefd9488190b8cdfa8543db8d31 |
completed | April 20, 2026, 4:57 p.m. |
| PD | Predicate disambiguation | batch_69e537f47c508190853c4e009c6b5566 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 10, 2026, 1:54 p.m.