Triple
T3874737
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Military Order of William |
E92471
|
entity |
| Predicate | gradeWithBreastBadge |
P23326
|
FINISHED |
| Object | Knight 3rd Class |
—
|
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: Knight 3rd Class | Statement: [Military Order of William, gradeWithBreastBadge, Knight 3rd Class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: gradeWithBreastBadge Context triple: [Military Order of William, gradeWithBreastBadge, Knight 3rd Class]
-
A.
bearsOnBreast
Indicates that one entity is depicted or represented as being carried or displayed on the breast or chest area of another entity.
-
B.
qualificationBadge
Indicates that an entity has been awarded or holds a specific qualification badge signifying a certified skill, status, or achievement.
-
C.
badge
Indicates that one entity confers, displays, or is associated with a symbolic mark or emblem representing status, achievement, role, or affiliation in relation to another entity.
-
D.
badgeText
Indicates that a visual badge or label is associated with an entity, displaying specific text content.
-
E.
rankGrade
chosen
Indicates the grade or level assigned to an entity within a ranking or evaluation 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_69aed967448c819086c4b358d37b25aa |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef1515c688190a38332aedeed8a76 |
completed | March 9, 2026, 4:12 p.m. |
| PD | Predicate disambiguation | batch_69aee7574c408190893e70bf80514838 |
completed | March 9, 2026, 3:29 p.m. |
Created at: March 9, 2026, 3:20 p.m.