Triple
T25602320
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ultrawrap |
E641817
|
entity |
| Predicate | hasNonFunctionalGoal |
P180689
|
FINISHED |
| Object | improve interoperability of data sources |
—
|
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: improve interoperability of data sources | Statement: [Ultrawrap, hasNonFunctionalGoal, improve interoperability of data sources]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNonFunctionalGoal Context triple: [Ultrawrap, hasNonFunctionalGoal, improve interoperability of data sources]
-
A.
hasOperationalGoal
Indicates that an entity is associated with a specific objective or target it aims to achieve through its operations or activities.
-
B.
hasPrimaryGoal
Indicates that an entity’s main or most important objective is the specified goal.
-
C.
hasFictionalGoal
Indicates that an entity is associated with a goal or objective that exists only within a fictional, imagined, or narrative context.
-
D.
nonGoal
Indicates that the referenced state, action, or outcome is explicitly not a goal or intended objective within the given context.
-
E.
hasGoalStructure
Indicates that an entity is associated with, or organized around, a specific goal-oriented structure or framework.
- 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_69e75dc6ccf081908d49578fd36a76d5 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f74c70fd248190a9d5543afcb08211 |
completed | May 3, 2026, 1:24 p.m. |
| PD | Predicate disambiguation | batch_69f7478e3b548190a51d5d436e2bb036 |
completed | May 3, 2026, 1:03 p.m. |
| PDg | Predicate description generation | batch_69f74c6fa6548190b03935f65429a24e |
completed | May 3, 2026, 1:23 p.m. |
Created at: April 21, 2026, 4:36 p.m.