Triple
T31792834
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Valorous Unit Award ribbon |
E811515
|
entity |
| Predicate | individualEquivalent |
P58587
|
FINISHED |
| Object | Silver Star |
—
|
NE NERFINISHED |
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: Silver Star | Statement: [Valorous Unit Award ribbon, individualEquivalent, Silver Star]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: individualEquivalent Context triple: [Valorous Unit Award ribbon, individualEquivalent, Silver Star]
-
A.
isYouthEquivalentOf
Indicates that one entity is the youth or junior counterpart of another, typically representing a younger or age-specific version of the same role, group, or category.
-
B.
maleEquivalent
Indicates that one entity is the corresponding male counterpart or equivalent of another entity.
-
C.
samePersonAs
Indicates that two referenced entities are in fact the very same individual, not just similar or related.
-
D.
equivalentIn
chosen
Indicates that two entities are considered logically or functionally the same in meaning, status, or effect within a given context.
-
E.
relationshipToHumans
Indicates the nature or type of connection, association, or relevance that something has specifically with humans.
- 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_69f348e60748819082dcaa7792659803 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ac1a37908190a1ad8005a8e5d2ae |
completed | May 3, 2026, 1:59 a.m. |
| PD | Predicate disambiguation | batch_69f6aa21f2508190a204a424ffc00ca6 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:39 p.m.