Triple
T36599992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CD22 |
E902890
|
entity |
| Predicate | ligandRecognizedOn |
P177104
|
FINISHED |
| Object | glycoproteins |
—
|
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: glycoproteins | Statement: [CD22, ligandRecognizedOn, glycoproteins]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: ligandRecognizedOn Context triple: [CD22, ligandRecognizedOn, glycoproteins]
-
A.
ligandType
Indicates the specific kind or category of ligand associated with, or acting upon, an entity in the relationship.
-
B.
hasLigand
chosen
Indicates that an entity is bound to, associated with, or interacts specifically with a particular ligand.
-
C.
ligandFamily
Indicates that one entity is a ligand belonging to the same functional or structural family as another entity.
-
D.
receptorTypeInteractedWith
Indicates that one entity has interacted with, bound to, or otherwise engaged a specific type of receptor.
-
E.
areRecognizedBy
Indicates that one entity acknowledges, identifies, or accepts another entity as valid, known, or legitimate.
- 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_69f76e66b7b88190848f7a3e1188915f |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7c371931c8190afb1d4dd5157f92c |
completed | May 3, 2026, 9:51 p.m. |
| PD | Predicate disambiguation | batch_69f7c1baf25c8190a78dd54a400d2c50 |
completed | May 3, 2026, 9:44 p.m. |
Created at: May 3, 2026, 4:11 p.m.