Triple
T26375085
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Prins van Waterloo |
E660875
|
entity |
| Predicate | titleHolderNationalityLink |
P179005
|
FINISHED |
| Object | British aristocracy |
—
|
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: British aristocracy | Statement: [Prins van Waterloo, titleHolderNationalityLink, British aristocracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderNationalityLink Context triple: [Prins van Waterloo, titleHolderNationalityLink, British aristocracy]
-
A.
titleHolderLaterNationality
Indicates that the person who held a particular title later acquired or changed to the specified nationality.
-
B.
leaderNationality
Indicates that a leader has a specific national affiliation or citizenship.
-
C.
ownerNationality
Indicates that the owner of an entity has the specified nationality.
-
D.
titleHolderBirthCountry
Indicates the country in which the holder of a particular title was born.
-
E.
officeHolderNationality
Indicates that the nationality of an office holder is a specified country or nation.
- 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_69ee812a698881908d6a58265995fa39 |
completed | April 26, 2026, 9:18 p.m. |
| NER | Named-entity recognition | batch_69f719cc31ec819099bebcf833b14d76 |
completed | May 3, 2026, 9:47 a.m. |
| PD | Predicate disambiguation | batch_69f71820c6c88190ab38b4fa626d22cc |
completed | May 3, 2026, 9:40 a.m. |
| PDg | Predicate description generation | batch_69f71995853c8190912025c0e83640c8 |
completed | May 3, 2026, 9:47 a.m. |
Created at: April 26, 2026, 11 p.m.