Triple
T23206932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Washington, D.C. street numbering system |
E580483
|
entity |
| Predicate | omitsLetter |
P4433
|
FINISHED |
| Object | I |
—
|
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: I | Statement: [Washington, D.C. street numbering system, omitsLetter, I]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: omitsLetter Context triple: [Washington, D.C. street numbering system, omitsLetter, I]
-
A.
excludesLetter
chosen
Indicates that one entity does not contain or allow the presence of a specified letter.
-
B.
avoidsPronunciationOf
Indicates that one entity deliberately refrains from saying or articulating the name, word, or expression associated with another entity.
-
C.
usesAdditionalLettersFrom
Indicates that one entity forms or derives its representation by incorporating extra letters taken from another entity beyond those originally present.
-
D.
usesSpecialLetterFor
Indicates that one entity employs a particular special letter or character specifically in relation to another entity.
-
E.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
- 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_69e24602ae1481908aaa6bc7ca493867 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f1907d8be08190a100d99efaff9964 |
completed | April 29, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_69effcccee508190a7ae311fdd319806 |
completed | April 28, 2026, 12:18 a.m. |
Created at: April 17, 2026, 4:07 p.m.