Triple
T7166900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gwendoline Mary Lacey |
E167091
|
entity |
| Predicate | hasSocioeconomicBackground |
P26434
|
FINISHED |
| Object | upper‑middle‑class |
—
|
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: upper‑middle‑class | Statement: [Gwendoline Mary Lacey, hasSocioeconomicBackground, upper‑middle‑class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSocioeconomicBackground Context triple: [Gwendoline Mary Lacey, hasSocioeconomicBackground, upper‑middle‑class]
-
A.
hasSocioeconomicIssue
Indicates that an entity is affected by, associated with, or involved in a socioeconomic problem or challenge.
-
B.
hasFamilyBackgroundIn
Indicates that an entity comes from, or is associated with, a particular familial or ancestral background.
-
C.
socialClassAtBirth
chosen
Indicates the social class or socioeconomic status into which an individual was born.
-
D.
economicStatus
Indicates the financial or socioeconomic condition or standing of an entity relative to others or to defined economic criteria.
-
E.
hasAcademicBackgroundIn
Indicates that an entity possesses formal education, training, or scholarly experience in a specified academic field or discipline.
- 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_69c68888c10c819095e0383020225758 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e85a07388190a07054ef12870fa1 |
completed | March 27, 2026, 8:28 p.m. |
| PD | Predicate disambiguation | batch_69c6e1cd5c948190a9113b23f7308c21 |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:48 p.m.