Triple
T30833547
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northwest street naming system of Washington, D.C. |
E785293
|
entity |
| Predicate | hasIrregularities |
P67395
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Northwest street naming system of Washington, D.C., hasIrregularities, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasIrregularities Context triple: [Northwest street naming system of Washington, D.C., hasIrregularities, yes]
-
A.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
B.
hasAberrationCharacteristics
Indicates that an entity exhibits traits or properties that deviate from what is considered normal, standard, or expected.
-
C.
hasIrregularShape
Indicates that an entity possesses a form or outline that deviates from a regular, standard, or symmetrical shape.
-
D.
hasAnomaly
chosen
Indicates that an entity exhibits, contains, or is associated with an irregular, abnormal, or unexpected condition or feature.
-
E.
hadMultipleIssues
Indicates that the subject experienced more than one problem, error, or issue in the relevant 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_69f224b73d8c81908129383bfb397c87 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f6913c10f881909fee1f70a4fe9ad0 |
completed | May 3, 2026, 12:05 a.m. |
| PD | Predicate disambiguation | batch_69f68b7d2794819092fef8a63f4f3de8 |
completed | May 2, 2026, 11:40 p.m. |
Created at: April 29, 2026, 8:45 p.m.