Triple
T3017827
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | None but the Lonely Heart |
E82378
|
entity |
| Predicate | hasSettingFeature |
P182
|
FINISHED |
| Object | working-class London neighborhoods |
—
|
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: working-class London neighborhoods | Statement: [None but the Lonely Heart, hasSettingFeature, working-class London neighborhoods]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettingFeature Context triple: [None but the Lonely Heart, hasSettingFeature, working-class London neighborhoods]
-
A.
hasSetting
Indicates that an entity takes place, occurs, or exists within a particular environment, context, or location.
-
B.
hasFeature
chosen
Indicates that an entity possesses, exhibits, or includes a particular characteristic, attribute, or component.
-
C.
hasNotableSettingBy
Indicates that the subject has a notable or significant setting that was created, designed, or established by the specified entity.
-
D.
supportsFeature
Indicates that one entity provides, enables, or is compatible with a particular feature or capability of another.
-
E.
hasFeatureID
Indicates that an entity is associated with a specific feature identified by a unique ID.
- 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_69ad8b1eb53481908c39bbcd1ec104b2 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9a90ea64819080620e60bbd6aa24 |
completed | March 8, 2026, 3:49 p.m. |
| PD | Predicate disambiguation | batch_69ad961a97188190809dc73430a8eda8 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 3 p.m.