Triple
T27586890
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CIQ |
E699708
|
entity |
| Predicate | usesSoftwareModel |
P174680
|
FINISHED |
| Object | open source |
—
|
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: open source | Statement: [CIQ, usesSoftwareModel, open source]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesSoftwareModel Context triple: [CIQ, usesSoftwareModel, open source]
-
A.
usesSoftware
Indicates that one entity employs or operates a particular software application or system to perform tasks or functions.
-
B.
hasSoftwareType
Indicates that an entity is associated with or classified under a particular type or category of software.
-
C.
hasSoftwareCompatibilityWith
Indicates that one software system can operate correctly and effectively with another software system, without conflicts or required modifications.
-
D.
usesProductionModel
Indicates that one entity employs or relies on another entity as its primary or official production model in practice.
-
E.
softwareModel
Indicates that one entity serves as a software-based representation or abstraction (a model) of another entity or system.
- 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_69ef6a4cb8b881909b3a8d630fd89df2 |
completed | April 27, 2026, 1:53 p.m. |
| NER | Named-entity recognition | batch_69f6c5b7e46081909975b05f7298cc0e |
completed | May 3, 2026, 3:49 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f23ae081909a52801266063a3c |
completed | May 3, 2026, 3:41 a.m. |
| PDg | Predicate description generation | batch_69f6c49069e48190a3486b6254a6645b |
completed | May 3, 2026, 3:44 a.m. |
Created at: April 27, 2026, 2:04 p.m.