Triple
T2060917
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Between Riverside and Crazy |
E45785
|
entity |
| Predicate | settingDetail |
P25484
|
FINISHED |
| Object | rent-controlled apartment on Riverside Drive |
—
|
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: rent-controlled apartment on Riverside Drive | Statement: [Between Riverside and Crazy, settingDetail, rent-controlled apartment on Riverside Drive]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: settingDetail Context triple: [Between Riverside and Crazy, settingDetail, rent-controlled apartment on Riverside Drive]
-
A.
setting
Indicates the place, time, or context in which an event, action, or interaction occurs.
-
B.
featuresSetting
Indicates that something includes, presents, or highlights a particular setting as a notable or primary aspect.
-
C.
settingDescription
chosen
Indicates the descriptive details or characteristics that define the context or environment in which something occurs.
-
D.
settingCategory
Indicates the classification or type of context in which something is set or configured (e.g., grouping settings under a common category).
-
E.
customizableBy
Indicates that one entity can be modified, configured, or tailored in some way by another entity.
- 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_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9d0ecf08190aec20338a6ba9911 |
completed | March 7, 2026, 5:38 a.m. |
| PD | Predicate disambiguation | batch_69abb7ad5a7c8190b92575d6053b3fb7 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:40 p.m.