Triple
T2379084
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Freedom Cup |
E46268
|
entity |
| Predicate | matchCategory |
P38353
|
FINISHED |
| Object | test match |
—
|
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: test match | Statement: [Freedom Cup, matchCategory, test match]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: matchCategory Context triple: [Freedom Cup, matchCategory, test match]
-
A.
uniformCategory
Indicates that two or more entities share the same classification or type within a defined category system.
-
B.
category
Indicates that one entity is classified as a member or type within the grouping or class defined by another entity.
-
C.
rankingCategory
Indicates the classification or type of ranking under which an entity is evaluated or ordered.
-
D.
hasCategoryOn
Indicates that something is assigned to or associated with a specific category within a given context or scope.
-
E.
settingCategory
Indicates the classification or type of context in which something is set or configured (e.g., grouping settings under a common category).
- 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_69a88a1554a48190a0180682bcf099be |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc7974aa481908799ef2f854d1c9d |
completed | March 7, 2026, 6:37 a.m. |
| PD | Predicate disambiguation | batch_69abc59f73f08190924a36d7d475d8f4 |
completed | March 7, 2026, 6:28 a.m. |
| PDg | Predicate description generation | batch_69abc6f4245881909282b3184a288e2a |
completed | March 7, 2026, 6:34 a.m. |
Created at: March 4, 2026, 7:57 p.m.