Triple
T34174060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1927 Schneider Trophy |
E876618
|
entity |
| Predicate | numberOfCompetingNations |
P2436
|
FINISHED |
| Object | 3 |
—
|
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: 3 | Statement: [1927 Schneider Trophy, numberOfCompetingNations, 3]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCompetingNations Context triple: [1927 Schneider Trophy, numberOfCompetingNations, 3]
-
A.
numberOfParticipatingNations
chosen
Indicates the total count of nations that take part in a specified event, activity, or context.
-
B.
numberOfCurrentNations
Indicates the total count of nations that currently exist or are recognized at a given point in time.
-
C.
numberOfOriginalNations
Indicates the count of distinct original nations associated with a given entity or context.
-
D.
competesForNation
Indicates that an entity participates in a competition or contest on behalf of a specified nation.
-
E.
countryRepresentedCount
Indicates the number of distinct countries that are represented or associated with a given entity.
- 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_69f349ad97ac8190bf1f17417c970e64 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:54 a.m.