Triple

T8738427
Position Surface form Disambiguated ID Type / Status
Subject Oto Melara E207441 entity
Predicate formerName P65 FINISHED
Object OTO
OTO was the former name of Oto Melara, an Italian defense company known for producing naval guns, artillery systems, and other military equipment.
 E754804 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: OTO | Statement: [Oto Melara, formerName, OTO]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: OTO
Context triple: [Oto Melara, formerName, OTO]
  • A. OTT
    OTT is the standard three-letter abbreviation used for the National Hockey League team, the Ottawa Senators.
  • B. OTA
    OTA is a premier Indian military training institution that prepares cadets for commissioning as officers in the Indian Army.
  • C. OT
    OT is the commonly used abbreviation for the Teide Observatory, a major astronomical research facility located on Tenerife in Spain’s Canary Islands.
  • D. OT
    OT is the abbreviation for Organisation Todt, the Nazi-era civil and military engineering group responsible for large-scale construction projects such as the Atlantic Wall.
  • E. OT
    OT is the station code for Oranienburger Tor, a Berlin U-Bahn station on the city’s central U6 line.
  • 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: OTO
Triple: [Oto Melara, formerName, OTO]
Generated description
OTO was the former name of Oto Melara, an Italian defense company known for producing naval guns, artillery systems, and other military equipment.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: OTO
Target entity description: OTO was the former name of Oto Melara, an Italian defense company known for producing naval guns, artillery systems, and other military equipment.
  • A. OTT
    OTT is the standard three-letter abbreviation used for the National Hockey League team, the Ottawa Senators.
  • B. OTA
    OTA is a premier Indian military training institution that prepares cadets for commissioning as officers in the Indian Army.
  • C. OT
    OT is the commonly used abbreviation for the Teide Observatory, a major astronomical research facility located on Tenerife in Spain’s Canary Islands.
  • D. OT
    OT is the abbreviation for Organisation Todt, the Nazi-era civil and military engineering group responsible for large-scale construction projects such as the Atlantic Wall.
  • E. OT
    OT is the station code for Oranienburger Tor, a Berlin U-Bahn station on the city’s central U6 line.
  • 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_69ca835a03a081909d4d4cd01a18c9fb completed March 30, 2026, 2:06 p.m.
NER Named-entity recognition batch_69cc5d470c8c81909ead395ef704c6ba completed March 31, 2026, 11:48 p.m.
NED1 Entity disambiguation (via context triple) batch_69cf42d5dd508190854fbbc2541aa819 completed April 3, 2026, 4:32 a.m.
NEDg Description generation batch_69cf440051bc8190ad9d649150187932 completed April 3, 2026, 4:37 a.m.
NED2 Entity disambiguation (via description) batch_69cf4473ee0081908ed22eb0d855d7dd completed April 3, 2026, 4:39 a.m.
Created at: March 30, 2026, 6:38 p.m.