Triple
T12900837
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Henrik Lissner |
E308604
|
entity |
| Predicate | softwareDesignFocus |
P532
|
FINISHED |
| Object | editor productivity |
—
|
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: editor productivity | Statement: [Henrik Lissner, softwareDesignFocus, editor productivity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: softwareDesignFocus Context triple: [Henrik Lissner, softwareDesignFocus, editor productivity]
-
A.
programmingFocus
Indicates a relationship where an entity’s primary attention, effort, or specialization is directed toward a particular area or aspect of programming.
-
B.
designPhilosophy
chosen
Indicates the guiding principles, values, or conceptual approach that shape how something is designed or created.
-
C.
programFocus
Indicates that an educational or training program is primarily oriented around or concentrated on a particular subject, theme, or objective.
-
D.
formerProgrammingFocus
Indicates that an entity previously concentrated on a particular programming-related area or activity, but no longer does so.
-
E.
deploymentFocus
Indicates the primary area, target, or aspect that a deployment is directed toward or concentrated on.
- 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_69d7bdf7c1f0819098102569a8d8cbf5 |
completed | April 9, 2026, 2:55 p.m. |
| NER | Named-entity recognition | batch_69d97180ee708190b60a3e58c42f764f |
completed | April 10, 2026, 9:54 p.m. |
| PD | Predicate disambiguation | batch_69d96fa776648190b9b5c30722ea50b6 |
completed | April 10, 2026, 9:46 p.m. |
Created at: April 9, 2026, 5:40 p.m.