Triple

T24045399
Position Surface form Disambiguated ID Type / Status
Subject Herbert C. Brown E595503 entity
Predicate sharedNobelPrizeWith P1859 FINISHED
Object Georg Wittig
Georg Wittig was a German chemist best known for developing the Wittig reaction, a key method for synthesizing alkenes that earned him a share of the 1979 Nobel Prize in Chemistry.
E1618289 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: Georg Wittig | Statement: [Herbert C. Brown, sharedNobelPrizeWith, Georg Wittig]
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: Georg Wittig
Triple: [Herbert C. Brown, sharedNobelPrizeWith, Georg Wittig]
Generated description
Georg Wittig was a German chemist best known for developing the Wittig reaction, a key method for synthesizing alkenes that earned him a share of the 1979 Nobel Prize in Chemistry.

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_69e288c06a908190899cad4531f32c9a completed April 17, 2026, 7:23 p.m.
NER Named-entity recognition batch_69f1d9c9391c819095ea6232fa872d5c completed April 29, 2026, 10:13 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0f965357f4819099e5f593f90d8f11 completed May 21, 2026, 11:33 p.m.
NEDg Description generation batch_6a0f973823ac819092f241755fe86bf2 completed May 21, 2026, 11:37 p.m.
NED2 Entity disambiguation (via description) batch_6a0f981441b08190a0076042748d92ea completed May 21, 2026, 11:41 p.m.
Created at: April 17, 2026, 10:13 p.m.