Triple
T2859303
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duke of Limburg |
E63278
|
entity |
| Predicate | hasTitleHolderRole |
P41897
|
FINISHED |
| Object | ruler of the Duchy of Limburg |
—
|
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: ruler of the Duchy of Limburg | Statement: [Duke of Limburg, hasTitleHolderRole, ruler of the Duchy of Limburg]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTitleHolderRole Context triple: [Duke of Limburg, hasTitleHolderRole, ruler of the Duchy of Limburg]
-
A.
hasTitleHolder
Indicates that one entity is the current or designated holder of a specific title, position, or honor associated with another entity.
-
B.
refersToTitleHolder
Indicates that one entity makes reference to, or designates, the entity that currently holds a specific title or position.
-
C.
hasTitleType
Indicates that an entity holds a specific kind or category of title (such as job title, honorific, or formal designation).
-
D.
titleHolderIs
chosen
Indicates that one entity currently holds or possesses a specific title associated with another entity.
-
E.
hasRepresentativeTitle
Indicates that an entity holds a formal title or designation that serves as its primary or most commonly used label or name.
- 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_69ab4c41e8c08190a9e8f5249cc12610 |
completed | March 6, 2026, 9:50 p.m. |
| NER | Named-entity recognition | batch_69abdf8aec3c8190a4168d8c916b5268 |
completed | March 7, 2026, 8:19 a.m. |
| PD | Predicate disambiguation | batch_69abdd10aef88190b750aae07e7df4dc |
completed | March 7, 2026, 8:08 a.m. |
Created at: March 6, 2026, 10:02 p.m.