Triple

T33205444

Position	Surface form	Disambiguated ID	Type / Status
Subject	tumor necrosis factor alpha	`E850005`	entity
Predicate	receptorFor	`P149276`	FINISHED
Object	TNFRSF1A TNFRSF1A is a cell surface receptor that mediates tumor necrosis factor alpha (TNF-α) signaling, playing a key role in inflammation, apoptosis, and immune regulation.	`E2042580`	NE FINISHED

How this triple was built (3 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]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: TNFRSF1A
Triple: [tumor necrosis factor alpha, receptorFor, TNFRSF1A]

Generated description

TNFRSF1A is a cell surface receptor that mediates tumor necrosis factor alpha (TNF-α) signaling, playing a key role in inflammation, apoptosis, and immune regulation.

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 (6 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.
NED1	Entity disambiguation (via context triple)	`batch_6a352fc40600819092779618431f0ec2`	completed	June 19, 2026, 12:02 p.m.
NEDg	Description generation	`batch_6a353033d4808190b4d8096162a14557`	completed	June 19, 2026, 12:04 p.m.
NED2	Entity disambiguation (via description)	`batch_6a353298f99c8190a2774b4aab087295`	completed	June 19, 2026, 12:14 p.m.
PD	Predicate disambiguation	`batch_69f6d82eaee081908f06a71546315aea`	completed	May 3, 2026, 5:07 a.m.

Created at: May 1, 2026, 1:30 a.m.