Triple
T22937204
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Queen of Prussia |
E569617
|
entity |
| Predicate | equivalentRole |
P7006
|
FINISHED |
| Object | queen consort |
—
|
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: queen consort | Statement: [Queen of Prussia, equivalentRole, queen consort]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: equivalentRole Context triple: [Queen of Prussia, equivalentRole, queen consort]
-
A.
hasEquivalentRole
chosen
Indicates that two entities hold roles that are functionally the same or interchangeable in a given context.
-
B.
equivalentTo
Indicates that two entities represent the same concept, value, or state, and can be treated as interchangeable in the given context.
-
C.
effectiveRole
Indicates the functional role or capacity an entity actually performs or holds in a given context, regardless of its formal or nominal designation.
-
D.
hasAdministrativeEquivalent
Indicates that two entities hold equivalent roles, powers, or status within an administrative or governance structure.
-
E.
roleSimilarTo
Indicates that two entities have roles or functions that are alike or closely comparable in nature or responsibility.
- 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_69e24590862c8190858f180ad302adab |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f1813608e48190922df7a5386dc391 |
completed | April 29, 2026, 3:55 a.m. |
| PD | Predicate disambiguation | batch_69ef3b882e708190b0eb0c87021c75b8 |
completed | April 27, 2026, 10:33 a.m. |
Created at: April 17, 2026, 3:45 p.m.