Triple
T22893074
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Gospel According to the Ghetto |
E568093
|
entity |
| Predicate | usesAsLens |
P150155
|
FINISHED |
| Object | lived experiences of the urban poor |
—
|
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: lived experiences of the urban poor | Statement: [The Gospel According to the Ghetto, usesAsLens, lived experiences of the urban poor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesAsLens Context triple: [The Gospel According to the Ghetto, usesAsLens, lived experiences of the urban poor]
-
A.
usesLensBrand
Indicates that one entity employs or operates using a lens produced by a specific brand.
-
B.
usesLensMount
Indicates that one device or component is designed to accept, attach to, or operate with a specific type of lens mount.
-
C.
usesOpticsType
Indicates that one entity employs or is characterized by a specific type of optical system or technology.
-
D.
lensType
Indicates the specific kind or category of lens associated with or used by an entity.
-
E.
effectOnLens
Indicates the influence or impact that one entity has on the properties, behavior, or performance of a lens.
- F. None of above. chosen
Provenance (4 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_69e2458c23ec81908fa2570692c6614f |
completed | April 17, 2026, 2:37 p.m. |
| NER | Named-entity recognition | batch_69f17fc76be48190af9aa54a84b2d7bf |
completed | April 29, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69ef3b6b2e2481908258156937b5a745 |
completed | April 27, 2026, 10:33 a.m. |
| PDg | Predicate description generation | batch_69ef538a115081908982597f79355840 |
completed | April 27, 2026, 12:16 p.m. |
Created at: April 17, 2026, 3:40 p.m.