Triple
T1484414
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. Secretary |
E29431
|
entity |
| Predicate | hasFormality |
P4035
|
FINISHED |
| Object | high |
—
|
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: high | Statement: [Mr. Secretary, hasFormality, high]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormality Context triple: [Mr. Secretary, hasFormality, high]
-
A.
formalityLevel
chosen
Indicates the degree of social or stylistic formality characterizing an interaction, expression, or context between entities.
-
B.
hasFormalStatus
Indicates that an entity possesses an officially recognized or legally defined status within a formal system or context.
-
C.
politenessLevel
Indicates the degree of courteousness or respectfulness expressed by one entity toward another in an interaction.
-
D.
formed
Indicates that one entity came into existence, shape, or organization as a result of the actions or processes involving another entity.
-
E.
formalFunction
Indicates that an entity serves an official or designated role or purpose within a formal structure, system, or context.
- 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_69a498da82e08190ba833330d05f380f |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c6a011f0819086e9ee517ed6d29f |
completed | March 1, 2026, 11:07 p.m. |
| PD | Predicate disambiguation | batch_69a4c486eacc81909c272f9bdf50a7c3 |
completed | March 1, 2026, 10:58 p.m. |
Created at: March 1, 2026, 8:12 p.m.