Triple
T20163947
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | New York Street Set (historical) |
E491781
|
entity |
| Predicate | hasSettingStyle |
P1609
|
FINISHED |
| Object | urban 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: urban street | Statement: [New York Street Set (historical), hasSettingStyle, urban street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettingStyle Context triple: [New York Street Set (historical), hasSettingStyle, urban street]
-
A.
hasStyle
chosen
Indicates that an entity possesses, exhibits, or is characterized by a particular style or manner.
-
B.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
C.
hasSystemStyle
Indicates that one entity is associated with, or characterized by, a particular system-defined style of another entity.
-
D.
hasUserSetting
Indicates that a user is associated with a specific configuration or preference setting.
-
E.
hasSettingRole
Indicates that an entity participates in a setting by fulfilling a specific contextual or functional role within it.
- 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_69da6266c6888190bc1a3ecf24814d34 |
completed | April 11, 2026, 3:01 p.m. |
| NER | Named-entity recognition | batch_69e66841b7d88190af3606f762d87b24 |
completed | April 20, 2026, 5:54 p.m. |
| PD | Predicate disambiguation | batch_69e55b0c11cc8190836d1eee5945f000 |
completed | April 19, 2026, 10:45 p.m. |
Created at: April 11, 2026, 11:35 p.m.