Triple
T26473006
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speaker pro tempore |
E665949
|
entity |
| Predicate | mayHaveVariantTitle |
P110696
|
FINISHED |
| Object | Acting Speaker pro tempore |
—
|
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: Acting Speaker pro tempore | Statement: [Speaker pro tempore, mayHaveVariantTitle, Acting Speaker pro tempore]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveVariantTitle Context triple: [Speaker pro tempore, mayHaveVariantTitle, Acting Speaker pro tempore]
-
A.
titleVariesBy
Indicates that the title associated with an entity changes depending on context, conditions, or another varying attribute.
-
B.
nameHasVariant
Indicates that an entity’s name has an alternative or variant form.
-
C.
hasWorkTitleVariant
Indicates that an entity has an alternative or variant form of its work title, such as a different wording, spelling, or language version of the same title.
-
D.
haveAlternativeTitle
chosen
Indicates that an entity is known by one or more alternative titles or names in addition to its primary title.
-
E.
titleVariant
Indicates that one title is an alternative or variant form of another title referring to the same work or 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_69ee883f80dc819090e311b022b78e02 |
completed | April 26, 2026, 9:48 p.m. |
| NER | Named-entity recognition | batch_69f61f12b0f08190bc4a16907941864c |
completed | May 2, 2026, 3:58 p.m. |
| PD | Predicate disambiguation | batch_69f61b3a8ae0819090189fbd8eb19f2f |
completed | May 2, 2026, 3:41 p.m. |
Created at: April 27, 2026, 12:21 a.m.