Triple

T23470275
Position Surface form Disambiguated ID Type / Status
Subject SEALAB II E569206 entity
Predicate projectDirector P11213 FINISHED
Object George F. Bond
George F. Bond was a pioneering U.S. Navy physician and undersea medicine specialist who helped develop saturation diving and led early experimental habitat projects like SEALAB.
E1624808 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: George F. Bond | Statement: [SEALAB II, projectDirector, George F. Bond]
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: George F. Bond
Triple: [SEALAB II, projectDirector, George F. Bond]
Generated description
George F. Bond was a pioneering U.S. Navy physician and undersea medicine specialist who helped develop saturation diving and led early experimental habitat projects like SEALAB.

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_69e2458ebd808190b3298163132cfb0b completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f1a6ff8dc0819086961b1f07030d9c completed April 29, 2026, 6:36 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0fbcdf737c8190b4b9496d05f50241 completed May 22, 2026, 2:18 a.m.
NEDg Description generation batch_6a0fbfe524888190b64ae696c2924b2e completed May 22, 2026, 2:31 a.m.
NED2 Entity disambiguation (via description) batch_6a0fc06a9f2481909c0e770b96664781 completed May 22, 2026, 2:33 a.m.
Created at: April 17, 2026, 5:54 p.m.