Triple
T2523516
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CB1 receptor |
E55578
|
entity |
| Predicate | bindsLigand |
P37017
|
FINISHED |
| Object | anandamide |
—
|
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: anandamide | Statement: [CB1 receptor, bindsLigand, anandamide]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bindsLigand Context triple: [CB1 receptor, bindsLigand, anandamide]
-
A.
hasProteinBinding
Indicates that one entity is capable of physically binding to or interacting specifically with a protein.
-
B.
bindsTo
chosen
Indicates that one entity physically or functionally attaches or connects to another, often with some specificity or selectivity in the interaction.
-
C.
hasBindingEnergy
Indicates that one entity possesses or is characterized by a specific amount of binding energy associated with its formation or stability.
-
D.
binding
Indicates that one entity physically or chemically attaches, adheres, or forms a stable association with another entity.
-
E.
hasMolecularTarget
Indicates that one entity (such as a drug or compound) is directed toward, binds to, or specifically interacts with a particular molecular target (such as a protein, receptor, or gene).
- 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_69ab49e4749c8190813311efd1630f1b |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd23a0a548190b44393e0f823f7a9 |
completed | March 7, 2026, 7:22 a.m. |
| PD | Predicate disambiguation | batch_69abd0c144b0819092f32a13c1d127e5 |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:46 p.m.