Triple
T32307673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle Efficiency "E" |
E825410
|
entity |
| Predicate | associatedMarkings |
P32310
|
FINISHED |
| Object | hash marks or service stripes for consecutive awards |
—
|
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: hash marks or service stripes for consecutive awards | Statement: [Battle Efficiency "E", associatedMarkings, hash marks or service stripes for consecutive awards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: associatedMarkings Context triple: [Battle Efficiency "E", associatedMarkings, hash marks or service stripes for consecutive awards]
-
A.
armorMarkings
Indicates that one entity bears specific markings, patterns, or insignia on its armor in relation to another entity or context.
-
B.
mayHaveMarkings
Indicates that an entity is permitted or able to possess certain markings or distinguishing signs.
-
C.
registrationMark
Indicates that an entity bears a specific official registration identifier or code assigned by an authority.
-
D.
distinctiveMarking
chosen
Indicates that one entity bears a unique or distinguishing visual feature or pattern that sets it apart from others.
-
E.
reportedMarks
Indicates that an entity has formally communicated or submitted the marks/grades of another entity (such as a student or assessment) to a relevant party or system.
- 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_69f3491213b88190a57094d8697a7455 |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_6a037c894b488190bcbec2eccaff4a01 |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379edf2d88190b492fca86ed23cac |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 12:45 a.m.