Triple
T6004934
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TARDBP |
E133685
|
entity |
| Predicate | hasProteinFeature |
P68686
|
FINISHED |
| Object | RNA recognition motif |
—
|
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: RNA recognition motif | Statement: [TARDBP, hasProteinFeature, RNA recognition motif]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProteinFeature Context triple: [TARDBP, hasProteinFeature, RNA recognition motif]
-
A.
hasProteinBinding
Indicates that one entity is capable of physically binding to or interacting specifically with a protein.
-
B.
proteinContent
Indicates the amount or proportion of protein present in a given entity or substance.
-
C.
hasFeatureCode
Indicates that an entity is associated with a specific feature identifier or code that characterizes one of its properties or attributes.
-
D.
hasPreclinicalFeature
Indicates that an entity exhibits a characteristic, sign, or attribute that is present before the full clinical manifestation of a condition or disease.
-
E.
hasLinguisticFeature
Indicates that an entity possesses a particular linguistic property, trait, or characteristic.
- 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_69c00872444c8190bfaf1739dcec765c |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c04f10d18081908c351170b7f58d3d |
completed | March 22, 2026, 8:20 p.m. |
| PD | Predicate disambiguation | batch_69c049e3316c819087ea635fa7ee8472 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8c5bfc8190b986a7071d1b23e3 |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:06 p.m.