Triple
T29724338
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Litening II |
E752137
|
entity |
| Predicate | improvementArea |
P163633
|
FINISHED |
| Object | targeting accuracy |
—
|
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: targeting accuracy | Statement: [Litening II, improvementArea, targeting accuracy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: improvementArea Context triple: [Litening II, improvementArea, targeting accuracy]
-
A.
improvementFocus
chosen
Indicates that an entity is specifically directed toward or concerned with making improvements to another entity or aspect.
-
B.
guidanceImprovement
Indicates that one entity provides direction, feedback, or support that helps another entity enhance or improve its performance, behavior, or outcomes.
-
C.
seeksToImprove
Indicates an intentional effort by one entity to make another entity or condition better than its current state.
-
D.
improvesIn
Indicates that one entity causes or contributes to an increase in quality, performance, or effectiveness in another entity or context.
-
E.
claimsToImprove
Indicates that one entity asserts or promises that it will enhance, benefit, or make another entity better in some way.
- 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_69f0d628c00c8190ab5ee7e423d7ec3c |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69f672fe1b2881909acfdfed7c4a1ac2 |
completed | May 2, 2026, 9:56 p.m. |
| PD | Predicate disambiguation | batch_69f6659f246081909821c5f452d14e8f |
completed | May 2, 2026, 8:59 p.m. |
Created at: April 28, 2026, 7:38 p.m.