Triple
T23737659
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Difference Engine No. 1 |
E586579
|
entity |
| Predicate | projectIssue |
P153485
|
FINISHED |
| Object | engineering difficulties |
—
|
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: engineering difficulties | Statement: [Difference Engine No. 1, projectIssue, engineering difficulties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: projectIssue Context triple: [Difference Engine No. 1, projectIssue, engineering difficulties]
-
A.
project
Indicates that an entity plans, organizes, or carries out a structured effort or initiative aimed at achieving a specific goal or outcome.
-
B.
programIssue
Indicates that there is a problem, defect, or malfunction associated with a program or software system.
-
C.
projectModel
Indicates a relationship where one entity serves as a model, template, or representation for a project or projected outcome involving another entity.
-
D.
worksOnIssue
Indicates that an entity (typically a person or team) is actively engaged in addressing, resolving, or contributing work toward a specific issue.
-
E.
issueNumber
Indicates the specific numeric identifier assigned to distinguish one issue from others within a series or collection.
- 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_69e24907dc9c8190be074c9c96a0ec2d |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1bad356c88190ae29ce403145ee73 |
completed | April 29, 2026, 8:01 a.m. |
| PD | Predicate disambiguation | batch_69f155f012808190a4b1cbc155558ade |
completed | April 29, 2026, 12:50 a.m. |
| PDg | Predicate description generation | batch_69f15adb23d88190ac2632299c26a9b3 |
completed | April 29, 2026, 1:11 a.m. |
Created at: April 17, 2026, 7:11 p.m.