Triple
T34606020
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Src family kinases |
E888596
|
entity |
| Predicate | hasConservedMotif |
P182389
|
FINISHED |
| Object | HRD motif in catalytic loop |
—
|
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: HRD motif in catalytic loop | Statement: [Src family kinases, hasConservedMotif, HRD motif in catalytic loop]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasConservedMotif Context triple: [Src family kinases, hasConservedMotif, HRD motif in catalytic loop]
-
A.
hasTypeOfMotif
chosen
Indicates that one entity features or is characterized by a specific kind or category of motif.
-
B.
hasInheritanceMotif
Indicates that one entity incorporates or exhibits a recurring pattern, theme, or feature derived from or passed down by another entity.
-
C.
hasSignalingMotif
Indicates that one entity contains or exhibits a specific molecular or structural motif involved in signaling processes related to another entity.
-
D.
numberOfMotifs
Indicates the count of distinct motifs associated with or contained within a given entity.
-
E.
hasMirrorMotif
Indicates that one entity features a mirror-related motif or pattern in relation to another entity or context.
- 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_69f349d489d48190ba30e7d97c6f5ef9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 2:03 a.m.