Triple
T9224339
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Irving Street NE |
E221641
|
entity |
| Predicate | hasAddressSystem |
P1216
|
FINISHED |
| Object | Washington, D.C. street addressing system |
—
|
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: Washington, D.C. street addressing system | Statement: [Irving Street NE, hasAddressSystem, Washington, D.C. street addressing system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAddressSystem Context triple: [Irving Street NE, hasAddressSystem, Washington, D.C. street addressing system]
-
A.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
B.
usesAddressingSystem
chosen
Indicates that one entity employs or applies a particular addressing system associated with another entity.
-
C.
hasAddressState
Indicates that an entity’s address is located within a particular state or state-level administrative region.
-
D.
hasPublicAddressSystem
Indicates that an entity is equipped with or includes a public address (PA) system for broadcasting audio announcements.
-
E.
addressedThrough
Indicates that an issue, request, or communication is handled, resolved, or processed by means of a specified channel, method, or intermediary.
- 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_69ca83ec8db08190a9110df8232885d2 |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccda9c71c4819089dcc3689f322529 |
completed | April 1, 2026, 8:43 a.m. |
| PD | Predicate disambiguation | batch_69cc7a3daeb481908b0abde3fbc1f1f0 |
completed | April 1, 2026, 1:51 a.m. |
Created at: March 30, 2026, 7:28 p.m.