Triple

T37030392
Position Surface form Disambiguated ID Type / Status
Subject Gwynne Shotwell E916473 entity
Predicate positionHeld P8 FINISHED
Object Chief Operating Officer of SpaceX
The Chief Operating Officer of SpaceX is the top executive responsible for overseeing the company’s day-to-day operations and execution of its commercial spaceflight and launch services strategy.
E2211608 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: Chief Operating Officer of SpaceX | Statement: [Gwynne Shotwell, positionHeld, Chief Operating Officer of SpaceX]
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: Chief Operating Officer of SpaceX
Triple: [Gwynne Shotwell, positionHeld, Chief Operating Officer of SpaceX]
Generated description
The Chief Operating Officer of SpaceX is the top executive responsible for overseeing the company’s day-to-day operations and execution of its commercial spaceflight and launch services strategy.

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_69f76e92c7648190bcfa277f64c71a21 completed May 3, 2026, 3:49 p.m.
NER Named-entity recognition batch_69fa00d864788190b5835296bd1b0152 completed May 5, 2026, 2:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a3e8c35cd848190a25c5ecb6d69bcb2 completed June 26, 2026, 2:27 p.m.
NEDg Description generation batch_6a3e9554e9ac8190a85c1023288d06cb completed June 26, 2026, 3:05 p.m.
NED2 Entity disambiguation (via description) batch_6a3eee15a128819083466663227c0dcf completed June 26, 2026, 9:24 p.m.
Created at: May 3, 2026, 4:14 p.m.