Triple
T7899359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | P2PKH |
E183408
|
entity |
| Predicate | addressExamplePrefix |
P79665
|
FINISHED |
| Object | 1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa |
—
|
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: 1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa | Statement: [P2PKH, addressExamplePrefix, 1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: addressExamplePrefix Context triple: [P2PKH, addressExamplePrefix, 1A1zP1eP5QGefi2DMPTfTL5SLmv7DivfNa]
-
A.
addressPrefix
Indicates that one address string serves as the starting portion or leading segment of another address.
-
B.
namePrefix
Indicates that one entity is a prefix or leading part of another entity’s name.
-
C.
hasPostalCodePrefix
Indicates that a location’s postal code begins with a specified sequence of characters.
-
D.
locationExample
Indicates that one entity serves as an example or illustrative instance of a particular location associated with another entity.
-
E.
addressFormat
Indicates the standardized structure or pattern in which an address’s components are arranged and written.
- 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_69ca828d13088190b222be7aa9f9315c |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb3a3dc2208190a6fea93b60b8daca |
completed | March 31, 2026, 3:06 a.m. |
| PD | Predicate disambiguation | batch_69cae92d94448190b4425bbfb64c658c |
completed | March 30, 2026, 9:20 p.m. |
| PDg | Predicate description generation | batch_69caf7882b048190baa333af9f698590 |
completed | March 30, 2026, 10:22 p.m. |
Created at: March 30, 2026, 5:01 p.m.