Triple
T32425658
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Boston’s Black community |
E828568
|
entity |
| Predicate | hasFacedIssue |
P90681
|
FINISHED |
| Object | residential segregation |
—
|
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: residential segregation | Statement: [Boston’s Black community, hasFacedIssue, residential segregation]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFacedIssue Context triple: [Boston’s Black community, hasFacedIssue, residential segregation]
-
A.
hadIssue
chosen
Indicates that an entity experienced, encountered, or was affected by a particular problem, defect, or difficulty.
-
B.
facingIssue
Indicates that an entity is currently experiencing, encountering, or dealing with a problem, difficulty, or obstacle.
-
C.
hadMultipleIssues
Indicates that the subject experienced more than one problem, error, or issue in the relevant context.
-
D.
hasIssueWith
Indicates that one entity experiences a problem, conflict, or concern related to another entity.
-
E.
hasOngoingIssues
Indicates that an entity is currently experiencing unresolved or continuing problems or difficulties.
- 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_69f3491b28bc8190b75cea7a507f337b |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69fd3a69f1e08190a11aed015bff0858 |
completed | May 8, 2026, 1:20 a.m. |
| PD | Predicate disambiguation | batch_69fd39124180819080ca7911d3515d6d |
completed | May 8, 2026, 1:14 a.m. |
Created at: May 1, 2026, 12:54 a.m.