Triple

T16412294
Position Surface form Disambiguated ID Type / Status
Subject Halstead Medal E398595 entity
Predicate namedAfter P63 FINISHED
Object John B. Halstead
John B. Halstead was a distinguished scholar and educator honored by having the Halstead Medal named after him.
E1636484 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: John B. Halstead | Statement: [Halstead Medal, namedAfter, John B. Halstead]
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: John B. Halstead
Triple: [Halstead Medal, namedAfter, John B. Halstead]
Generated description
John B. Halstead was a distinguished scholar and educator honored by having the Halstead Medal named after him.

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_69d87f2950248190bc8ad9b9bebdc8c8 completed April 10, 2026, 4:40 a.m.
NER Named-entity recognition batch_69e32874a0cc8190874aea10b1d13004 completed April 18, 2026, 6:45 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fe3285c288190a1b9ab26c5bd4e75 completed May 22, 2026, 5:01 a.m.
NEDg Description generation batch_6a0fe4904b988190baba9eec573140bd completed May 22, 2026, 5:07 a.m.
NED2 Entity disambiguation (via description) batch_6a0fe523e5648190bde36809c67adb54 completed May 22, 2026, 5:09 a.m.
Created at: April 10, 2026, 5:09 a.m.