Triple
T9080476
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Lauenburg |
E217605
|
entity |
| Predicate | honorificPurpose |
P33845
|
FINISHED |
| Object | reward for political service |
—
|
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: reward for political service | Statement: [Duke of Lauenburg, honorificPurpose, reward for political service]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honorificPurpose Context triple: [Duke of Lauenburg, honorificPurpose, reward for political service]
-
A.
honorificSense
Indicates that one entity refers to another using an honorific or respectful linguistic form.
-
B.
honorificType
Indicates the type or category of honorific or formal title associated with an entity in a given context.
-
C.
reasonForHonorific
chosen
Indicates the reason, justification, or basis for which an honorific title or form of address is granted to or used for an entity.
-
D.
honorificIndicates
Indicates that one entity uses an honorific title or respectful form of address to refer to or address another entity.
-
E.
honorificFunction
Indicates that one entity serves as an honorific title, role, or form of address used in reference to 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_69ca83d7a0388190ba1af89ed7ba36f9 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69cc9607942c8190a21620892ce3cbe5 |
completed | April 1, 2026, 3:50 a.m. |
| PD | Predicate disambiguation | batch_69cc65fa79bc81908b46f05c8bba920f |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:13 p.m.