Triple
T30833526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Northwest street naming system of Washington, D.C. |
E785293
|
entity |
| Predicate | skipsLetter |
P4433
|
FINISHED |
| Object | J |
—
|
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: J | Statement: [Northwest street naming system of Washington, D.C., skipsLetter, J]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: skipsLetter Context triple: [Northwest street naming system of Washington, D.C., skipsLetter, J]
-
A.
excludesLetter
chosen
Indicates that one entity does not contain or allow the presence of a specified letter.
-
B.
followsLetter
Indicates that one element in a sequence comes immediately after another element in alphabetical or ordered letter arrangement.
-
C.
precedesLetter
Indicates that one letter comes immediately before another letter in a specified ordering, such as the alphabet or a given sequence.
-
D.
hasLetter
Indicates that one entity contains, includes, or is associated with a specific letter or character.
-
E.
subsequentLettersIndicate
Indicates that the letters immediately following a given position or symbol convey or specify additional information related to that position or symbol.
- 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.