Triple
T6949153
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Speaker of the Legislative Assembly |
E160875
|
entity |
| Predicate | mayHaveTitle |
P45332
|
FINISHED |
| Object | The Honorable Speaker |
—
|
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: The Honorable Speaker | Statement: [Speaker of the Legislative Assembly, mayHaveTitle, The Honorable Speaker]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mayHaveTitle Context triple: [Speaker of the Legislative Assembly, mayHaveTitle, The Honorable Speaker]
-
A.
mayBeTitled
chosen
Indicates that an entity can optionally bear or be assigned a particular title, but is not required to have it.
-
B.
hadTitle
Indicates that an entity held or was assigned a specific title or formal designation.
-
C.
usesTitle
Indicates that one entity refers to or addresses another entity using a specific title or formal designation.
-
D.
hasTitleIn
Indicates that an entity holds or is associated with a specific title within a particular context, domain, or language.
-
E.
containsTitle
Indicates that one entity includes or holds another entity’s title as part of its content or metadata.
- 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_69c68850419081909fb426b8f5a304c7 |
completed | March 27, 2026, 1:38 p.m. |
| NER | Named-entity recognition | batch_69c6dacca12481908942ba793a104cc3 |
completed | March 27, 2026, 7:30 p.m. |
| PD | Predicate disambiguation | batch_69c6d7bf0a7c8190b5ed4aca22ba9b97 |
completed | March 27, 2026, 7:17 p.m. |
Created at: March 27, 2026, 2:28 p.m.