Triple
T16451121
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Major League Baseball venues |
E399551
|
entity |
| Predicate | hasRegulationFieldShape |
P122841
|
FINISHED |
| Object | diamond |
—
|
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: diamond | Statement: [Major League Baseball venues, hasRegulationFieldShape, diamond]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRegulationFieldShape Context triple: [Major League Baseball venues, hasRegulationFieldShape, diamond]
-
A.
hasFieldFormation
Indicates that an entity possesses or exhibits a particular field formation, such as a structured arrangement or configuration of fields.
-
B.
regulatoryField
Indicates that one entity operates within, is governed by, or is associated with a particular area or domain of regulation defined by another entity.
-
C.
hasSquareShape
Indicates that an entity possesses a square geometric shape, typically having four equal sides and four right angles.
-
D.
hasRegulationSize
Indicates that something conforms to an officially defined or standard size specified by rules or regulations.
-
E.
hasShapeModel
Indicates that an entity is associated with a specific geometric or structural shape model that represents its form.
- 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_69d87f2c6778819080fcfae53be8f12a |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e32ce06de0819086eea241c6b32223 |
completed | April 18, 2026, 7:04 a.m. |
| PD | Predicate disambiguation | batch_69e227048d608190a4205eae3117629a |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24556c1348190902a4d116c3137d9 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:10 a.m.