Triple
T10456343
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | bridgeOS |
E246560
|
entity |
| Predicate | codebaseRelation |
P94142
|
FINISHED |
| Object | shares components with iOS |
—
|
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: shares components with iOS | Statement: [bridgeOS, codebaseRelation, shares components with iOS]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: codebaseRelation Context triple: [bridgeOS, codebaseRelation, shares components with iOS]
-
A.
datumRelation
Indicates a relationship where one piece of data is connected to, derived from, or otherwise associated with another piece of data.
-
B.
hasRelation
Indicates that there exists some specified relationship or association between two entities.
-
C.
subjectRelation
Indicates that one entity stands in a specified relational role or connection to another entity.
-
D.
cloneRelation
Indicates that one entity is a clone or exact copy derived from another entity.
-
E.
valueRelation
Indicates a comparative or associative relationship between the values or magnitudes of two or more entities.
- 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_69d381c04fe08190957c26c526a3b05a |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d4fe498a808190b88530f0221df4a6 |
completed | April 7, 2026, 12:53 p.m. |
| PD | Predicate disambiguation | batch_69d4fb7d353c8190a73f439a956c7606 |
completed | April 7, 2026, 12:41 p.m. |
| PDg | Predicate description generation | batch_69d4fe058fcc81909428137d9ffd6d90 |
completed | April 7, 2026, 12:52 p.m. |
Created at: April 6, 2026, 12:18 p.m.