Triple
T19155803
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Madam Deputy Prime Minister |
E468923
|
entity |
| Predicate | addressFormality |
P79413
|
FINISHED |
| Object | third-person reference |
—
|
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: third-person reference | Statement: [Madam Deputy Prime Minister, addressFormality, third-person reference]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressFormality Context triple: [Madam Deputy Prime Minister, addressFormality, third-person reference]
-
A.
addressFormat
Indicates the standardized structure or pattern in which an address’s components are arranged and written.
-
B.
addressingType
chosen
Indicates the manner or form in which one entity addresses or refers to another (e.g., formally, informally, by title, or by name).
-
C.
addressFormFor
Indicates the form of address or mode of speaking that one entity should use when referring to or speaking to another entity.
-
D.
formalityLevel
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
E.
titleFormality
Indicates the degree of formality conveyed by a title used to address or refer to an 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_69d8dd084ff48190ac0f8c46ee722629 |
completed | April 10, 2026, 11:20 a.m. |
| NER | Named-entity recognition | batch_69e5eeb914248190a92dc5f30cbc8fcc |
completed | April 20, 2026, 9:15 a.m. |
| PD | Predicate disambiguation | batch_69e4b9b475d88190a8c15e8eb01dbfef |
completed | April 19, 2026, 11:17 a.m. |
Created at: April 10, 2026, 12:06 p.m.