Triple
T8638552
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hero of the Republic of Cuba |
E204583
|
entity |
| Predicate | hasPhysicalRepresentation |
P103
|
FINISHED |
| Object | medal |
—
|
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: medal | Statement: [Hero of the Republic of Cuba, hasPhysicalRepresentation, medal]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalRepresentation Context triple: [Hero of the Republic of Cuba, hasPhysicalRepresentation, medal]
-
A.
isPhysicalArtifact
Indicates that the subject is a tangible, man-made object that physically exists in the real world.
-
B.
hasPhysicalNature
Indicates that one entity possesses or exhibits a specific physical form, composition, or material nature in relation to another.
-
C.
hasRealModel
Indicates that an abstract, theoretical, or simplified entity is associated with a corresponding concrete or physically instantiated model in the real world.
-
D.
hasPhysicalFootprint
Indicates that one entity occupies or affects a specific physical area or space in the real world.
-
E.
hasRepresentationIn
chosen
Indicates that one entity is represented, depicted, or encoded within another entity, such as a concept, object, or data structure having a corresponding representation in a specific medium or context.
- 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_69ca834ca1c88190a11ffb0200342fac |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc47944d1c819081f448f14d04bf9d |
completed | March 31, 2026, 10:15 p.m. |
| PD | Predicate disambiguation | batch_69cc455d6d448190a2da2a319ac78c37 |
completed | March 31, 2026, 10:06 p.m. |
Created at: March 30, 2026, 6:28 p.m.