Triple
T12173073
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michelle Sinclair |
E290018
|
entity |
| Predicate | socialIssueAssociatedWith |
P29037
|
FINISHED |
| Object | sex work and higher education costs |
—
|
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: sex work and higher education costs | Statement: [Michelle Sinclair, socialIssueAssociatedWith, sex work and higher education costs]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: socialIssueAssociatedWith Context triple: [Michelle Sinclair, socialIssueAssociatedWith, sex work and higher education costs]
-
A.
socialIssue
Indicates a relationship where something is recognized or treated as a problem or concern affecting society or a community at large.
-
B.
socialConcern
Indicates a relationship where an entity is concerned about, attentive to, or actively engaged with social issues, problems, or well-being.
-
C.
socialImpact
Indicates the extent to which an action, entity, or relationship affects society or communities, whether positively or negatively.
-
D.
politicalIssueIn
Indicates that a political issue is relevant to, occurs within, or is associated with a particular geographic or political region.
-
E.
involvesIssue
chosen
Indicates that an action, event, or entity is related to, concerns, or includes a particular issue.
- 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_69d6ab4d6c00819095a9a7c35de83cfb |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d91621ca6c81908365732f361aef13 |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150e85348190b9b47cda4a17dcd0 |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:50 p.m.