Triple
T33205444
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | tumor necrosis factor alpha |
E850005
|
entity |
| Predicate | receptorFor |
P149276
|
FINISHED |
| Object | TNFRSF1A |
—
|
NE NERFINISHED |
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: TNFRSF1A | Statement: [tumor necrosis factor alpha, receptorFor, TNFRSF1A]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: receptorFor Context triple: [tumor necrosis factor alpha, receptorFor, TNFRSF1A]
-
A.
receptorInput
Indicates that a receptor receives or is provided with an input signal or stimulus from another entity.
-
B.
receptor
chosen
Indicates that one entity functions as a receptor for another, typically binding or receiving a signal, substance, or stimulus from it.
-
C.
receptorSystem
Indicates that one entity functions as a receptor system through which another entity receives, processes, or responds to signals or stimuli.
-
D.
receptorTypeAtEffector
Indicates that a specific type of receptor is present at, or associated with, a particular effector site or effector cell.
-
E.
targetsReceptor
Indicates that one entity is directed toward, binds to, or is designed to act upon a specific receptor.
- 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_69f3495efedc8190843a5728089544b9 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f6dd3cc0648190a275812d6711275a |
completed | May 3, 2026, 5:29 a.m. |
| PD | Predicate disambiguation | batch_69f6d82eaee081908f06a71546315aea |
completed | May 3, 2026, 5:07 a.m. |
Created at: May 1, 2026, 1:30 a.m.