Triple

T37253357
Position Surface form Disambiguated ID Type / Status
Subject Israel Isaac Rabi E924055 entity
Predicate awardReceived P11 FINISHED
Object Nobel Prize in Physics 1944
The Nobel Prize in Physics 1944 was awarded for pioneering work in nuclear magnetic resonance, a discovery that later became fundamental to technologies such as MRI.
 E2219380 NE 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: Nobel Prize in Physics 1944 | Statement: [Israel Isaac Rabi, awardReceived, Nobel Prize in Physics 1944]
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: Nobel Prize in Physics 1944
Triple: [Israel Isaac Rabi, awardReceived, Nobel Prize in Physics 1944]
Generated description
The Nobel Prize in Physics 1944 was awarded for pioneering work in nuclear magnetic resonance, a discovery that later became fundamental to technologies such as MRI.

Provenance (5 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_69f76eaabb4c819093b751b139dad551 completed May 3, 2026, 3:50 p.m.
NER Named-entity recognition batch_69fb3729c6e481909a375336128176f5 completed May 6, 2026, 12:42 p.m.
NED1 Entity disambiguation (via context triple) batch_6a4043d3bb4c81908b62cff2c9f27271 completed June 27, 2026, 9:42 p.m.
NEDg Description generation batch_6a4044fd17208190b590493419679ef1 completed June 27, 2026, 9:47 p.m.
NED2 Entity disambiguation (via description) batch_6a4046ed8adc81909bb53bad47859232 completed June 27, 2026, 9:55 p.m.
Created at: May 3, 2026, 4:15 p.m.