Triple

T6324780
Position Surface form Disambiguated ID Type / Status
Subject José Antonio Ortega Lara E141835 entity
Predicate victimOf P870 FINISHED
Object ETA
ETA was a Basque separatist militant organization in Spain known for its decades-long campaign of bombings, assassinations, and kidnappings.
 E583548 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: ETA | Statement: [José Antonio Ortega Lara, victimOf, ETA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ETA
Context triple: [José Antonio Ortega Lara, victimOf, ETA]
  • A. ETA
    ETA is a U.S. Department of Labor agency that oversees federal employment, job training, and workforce development programs.
  • B. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • C. ETO
    ETO refers to the European Theater of Operations, the major area of military conflict in Europe during World War II involving the Allied and Axis powers.
  • D. ETO
    ETO is the stock ticker symbol for Entertainment One, a media and entertainment company known for producing and distributing film, television, and family programming.
  • E. ETAF
    ETAF is the acronym for the Ethiopian Air Force, the aerial warfare branch of Ethiopia’s military responsible for air defense and support operations.
  • 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: ETA
Triple: [José Antonio Ortega Lara, victimOf, ETA]
Generated description
ETA was a Basque separatist militant organization in Spain known for its decades-long campaign of bombings, assassinations, and kidnappings.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ETA
Target entity description: ETA was a Basque separatist militant organization in Spain known for its decades-long campaign of bombings, assassinations, and kidnappings.
  • A. ETA
    ETA is a U.S. Department of Labor agency that oversees federal employment, job training, and workforce development programs.
  • B. ETAC
    ETAC is the Engineering Technology Accreditation Commission of ABET, responsible for accrediting engineering technology degree programs worldwide.
  • C. ETO
    ETO refers to the European Theater of Operations, the major area of military conflict in Europe during World War II involving the Allied and Axis powers.
  • D. ETO
    ETO is the stock ticker symbol for Entertainment One, a media and entertainment company known for producing and distributing film, television, and family programming.
  • E. ETAF
    ETAF is the acronym for the Ethiopian Air Force, the aerial warfare branch of Ethiopia’s military responsible for air defense and support operations.
  • 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_69c008d201748190917e69c41ba3f978 completed March 22, 2026, 3:20 p.m.
NER Named-entity recognition batch_69c064e538ac81908c5d7556513c2bc3 completed March 22, 2026, 9:53 p.m.
NED1 Entity disambiguation (via context triple) batch_69c5e4960ac08190bcdebde8a607d2b5 completed March 27, 2026, 1:59 a.m.
NEDg Description generation batch_69c5e6a948c881909fa3d78408125c04 completed March 27, 2026, 2:08 a.m.
NED2 Entity disambiguation (via description) batch_69c5e713ea5c81908aeb6c5776f0ae10 completed March 27, 2026, 2:10 a.m.
Created at: March 22, 2026, 4:29 p.m.