Triple
T17453318
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 1995 U.S. Open Cup |
E424968
|
entity |
| Predicate | isEditionNumber |
P2681
|
FINISHED |
| Object | 82 |
—
|
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: 82 | Statement: [1995 U.S. Open Cup, isEditionNumber, 82]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isEditionNumber Context triple: [1995 U.S. Open Cup, isEditionNumber, 82]
-
A.
editionNumber
chosen
Indicates the specific sequential number assigned to an edition of a work within its series of published versions.
-
B.
numberOfEditions
Indicates the total count of distinct editions associated with a given entity.
-
C.
hasEditionIn
Indicates that one entity has a specific edition or version that exists or is available in another entity (such as a particular format, language, or location).
-
D.
hasEditionType
Indicates that one entity is a specific edition type or format classification of another entity (such as a work, publication, or product).
-
E.
isFirstEditionOf
Indicates that one entity is the original first published edition of another work or publication.
- 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_69d889db0ba481908402409af3b37917 |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e451406c748190b5ac6aacff7a3cc7 |
completed | April 19, 2026, 3:51 a.m. |
| PD | Predicate disambiguation | batch_69e3b4f0e3fc819094e466b74622c956 |
completed | April 18, 2026, 4:44 p.m. |
Created at: April 10, 2026, 5:47 a.m.