Triple
T995083
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | German Cross in Gold |
E21476
|
entity |
| Predicate | typicalRecipientRank |
P7007
|
FINISHED |
| Object | company-grade officers |
—
|
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: company-grade officers | Statement: [German Cross in Gold, typicalRecipientRank, company-grade officers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalRecipientRank Context triple: [German Cross in Gold, typicalRecipientRank, company-grade officers]
-
A.
typicalNumberOfRecipientsPerYear
Indicates the usual or average count of recipients involved in or affected by something within a one-year period.
-
B.
typicallyHoldsRank
chosen
Indicates that an entity is most commonly or usually associated with holding a particular rank or level in a hierarchy.
-
C.
eligibleRank
Indicates that an entity meets the required rank or level criteria to qualify for a specific role, action, or benefit.
-
D.
numberOfRankedPeople
Indicates the total count of people who have been assigned a rank within a given context or system.
-
E.
usesRank
Indicates that one entity applies or relies on a ranking or ordered level system associated with another entity.
- 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_69a493c476b48190b41fc5e793171cc6 |
completed | March 1, 2026, 7:30 p.m. |
| NER | Named-entity recognition | batch_69a4b4c75de88190bf7fec7a053f7a90 |
completed | March 1, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69a4b2af071c819086c374a16307dfe0 |
completed | March 1, 2026, 9:42 p.m. |
Created at: March 1, 2026, 7:41 p.m.