Triple
T3699941
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Duchess of Limburg |
E78551
|
entity |
| Predicate | successorTitleContext |
P49470
|
FINISHED |
| Object | titles of the Dutch royal house |
—
|
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: titles of the Dutch royal house | Statement: [Duchess of Limburg, successorTitleContext, titles of the Dutch royal house]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: successorTitleContext Context triple: [Duchess of Limburg, successorTitleContext, titles of the Dutch royal house]
-
A.
successorTitle
Indicates the title or position that directly follows and replaces a previous one in a sequence or succession.
-
B.
successorTitleIntegratedInto
Indicates that the title of a successor entity has been merged into and is now part of another title or entity.
-
C.
predecessorTitleHolder
Indicates that one entity previously held a particular title or position before another entity.
-
D.
successorContext
Indicates that one context directly follows and continues from another in a sequence or process.
-
E.
nicknameOfSuccessor
Indicates that one entity is a nickname or informal name used to refer to another entity that is its successor.
- F. None of above. chosen
Provenance (4 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_69ad85e3b1888190abc983e06968696d |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adc513d26c8190bfdf25f62af8c6ca |
completed | March 8, 2026, 6:50 p.m. |
| PD | Predicate disambiguation | batch_69adb84dc5808190850aa6975cb09e27 |
completed | March 8, 2026, 5:56 p.m. |
| PDg | Predicate description generation | batch_69adb903be308190a8f1925f99e67c68 |
completed | March 8, 2026, 5:59 p.m. |
Created at: March 8, 2026, 3:26 p.m.