Triple
T30833542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northwest street naming system of Washington, D.C. |
E785293
|
entity |
| Predicate | usesSuffixes |
P185322
|
FINISHED |
| Object | Street |
—
|
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: Street | Statement: [Northwest street naming system of Washington, D.C., usesSuffixes, Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSuffixes Context triple: [Northwest street naming system of Washington, D.C., usesSuffixes, Street]
-
A.
usedAsSuffixTo
Indicates that one entity functions as a suffix appended to another entity, typically to modify or extend its meaning.
-
B.
usesAffixation
Indicates that one entity forms or modifies another by adding affixes (such as prefixes, suffixes, infixes, or circumfixes) to it.
-
C.
hasVerbalSuffixes
Indicates that a language, word, or grammatical form possesses specific suffixes that are attached to verbs.
-
D.
usesDomainSuffix
Indicates that one entity employs or relies on a specific domain suffix (e.g., in URLs or identifiers) associated with another entity.
-
E.
hasNameSuffix
Indicates that an entity’s name includes a specific suffix or ending component.
- 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_69f224b73d8c81908129383bfb397c87 |
completed | April 29, 2026, 3:33 p.m. |
| NER | Named-entity recognition | batch_69f7be53890081909b1d93f30a8f31c6 |
completed | May 3, 2026, 9:29 p.m. |
| PD | Predicate disambiguation | batch_69f7bccacbac8190978976324c67db28 |
completed | May 3, 2026, 9:23 p.m. |
| PDg | Predicate description generation | batch_69f7be520f148190ba200bf3dbf40656 |
completed | May 3, 2026, 9:29 p.m. |
Created at: April 29, 2026, 8:45 p.m.