Triple
T58424
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mr. President |
E1156
|
entity |
| Predicate | addressType |
P3330
|
FINISHED |
| Object | second-person address |
—
|
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: second-person address | Statement: [Mr. President, addressType, second-person address]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressType Context triple: [Mr. President, addressType, second-person address]
-
A.
address
Indicates that one entity directs spoken or written communication specifically to another entity.
-
B.
addresses
Indicates that one entity directs speech, communication, or written correspondence specifically toward another entity.
-
C.
streetAddress
Indicates the specific location of an entity in terms of its numbered building and street name within a postal address.
-
D.
usesAddressingSystem
Indicates that one entity employs or applies a particular addressing system associated with another entity.
-
E.
nameType
Indicates the specific category or type of a name associated with an entity (e.g., legal name, nickname, alias, or preferred name).
- F. None of above. chosen
Provenance (4 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24c9057348190aa6692eeeae19569 |
completed | Feb. 28, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69a24ac7547c81909bb68f327cdb9158 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24c8fa20c8190aacc38e53d1f654c |
completed | Feb. 28, 2026, 2:01 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.