Triple

T13625199
Position Surface form Disambiguated ID Type / Status
Subject Uber Advanced Technologies Group E325559 entity
Predicate acquiredCompany P16131 FINISHED
Object Otto
Otto was a self-driving truck startup focused on autonomous freight technology, later integrated into Uber’s autonomous vehicle efforts.
 E1051245 NE FINISHED

How this triple was built (4 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: Otto | Statement: [Uber Advanced Technologies Group, acquiredCompany, Otto]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Otto
Context triple: [Uber Advanced Technologies Group, acquiredCompany, Otto]
  • A. Otto
    Otto is the title of one of the early nominative reports that were later incorporated into the official United States Reports, documenting decisions of the U.S. Supreme Court.
  • B. Otto
    Otto is the central German soldier protagonist in the 1993 war film "Stalingrad," whose experiences depict the brutality and futility of the Eastern Front in World War II.
  • C. Otto
    Otto is a given name of Germanic origin commonly used across various European countries.
  • D. Otto
    Otto was a lesser-known medieval Polish prince from the Piast dynasty, notable mainly as a younger son of Duke Casimir I the Restorer.
  • E. Otto
    Otto is one of the official mascots created for the 2002 Winter Olympics held in Salt Lake City.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Otto
Triple: [Uber Advanced Technologies Group, acquiredCompany, Otto]
Generated description
Otto was a self-driving truck startup focused on autonomous freight technology, later integrated into Uber’s autonomous vehicle efforts.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Otto
Target entity description: Otto was a self-driving truck startup focused on autonomous freight technology, later integrated into Uber’s autonomous vehicle efforts.
  • A. Otto
    Otto is the title of one of the early nominative reports that were later incorporated into the official United States Reports, documenting decisions of the U.S. Supreme Court.
  • B. Otto
    Otto is the central German soldier protagonist in the 1993 war film "Stalingrad," whose experiences depict the brutality and futility of the Eastern Front in World War II.
  • C. Otto
    Otto is a given name of Germanic origin commonly used across various European countries.
  • D. Otto
    Otto is one of the official mascots created for the 2002 Winter Olympics held in Salt Lake City.
  • E. Otto
    Otto was a lesser-known medieval Polish prince from the Piast dynasty, notable mainly as a younger son of Duke Casimir I the Restorer.
  • F. None of above. chosen

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_69d8076aae28819092cf636190ee5529 completed April 9, 2026, 8:09 p.m.
NER Named-entity recognition batch_69dbbe9c72c88190be3d7a3f2e96afbc completed April 12, 2026, 3:47 p.m.
NED1 Entity disambiguation (via context triple) batch_69f77fa4c5fc8190bd791f181fce2aa1 completed May 3, 2026, 5:02 p.m.
NEDg Description generation batch_69f78070e95c819088982e26fe2d8e26 completed May 3, 2026, 5:05 p.m.
NED2 Entity disambiguation (via description) batch_69f78157b9cc8190a1855cb9715aa7d5 completed May 3, 2026, 5:09 p.m.
Created at: April 9, 2026, 9:50 p.m.