Triple

T7464239
Position Surface form Disambiguated ID Type / Status
Subject Leslie E. Robertson Associates E176331 entity
Predicate abbreviation P43 FINISHED
Object LERA
LERA is a renowned structural engineering firm known for its innovative design of complex and iconic buildings and long-span structures worldwide.
 E666404 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: LERA | Statement: [Leslie E. Robertson Associates, abbreviation, LERA]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LERA
Context triple: [Leslie E. Robertson Associates, abbreviation, LERA]
  • A. LERU
    LERU is a consortium of leading European research-intensive universities that collaborates to influence research policy and promote high-quality academic research and education in Europe.
  • B. LEPA
    LEPA is the ICAO airport code for Palma de Mallorca Airport, a major international airport in Spain’s Balearic Islands.
  • C. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • D. LEAL
    LEAL is the ICAO airport code for Alicante–Elche Airport, the main international airport serving Spain’s Costa Blanca region.
  • E. Lela
    Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
  • 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: LERA
Triple: [Leslie E. Robertson Associates, abbreviation, LERA]
Generated description
LERA is a renowned structural engineering firm known for its innovative design of complex and iconic buildings and long-span structures worldwide.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LERA
Target entity description: LERA is a renowned structural engineering firm known for its innovative design of complex and iconic buildings and long-span structures worldwide.
  • A. LERU
    LERU is a consortium of leading European research-intensive universities that collaborates to influence research policy and promote high-quality academic research and education in Europe.
  • B. LEPA
    LEPA is the ICAO airport code for Palma de Mallorca Airport, a major international airport in Spain’s Balearic Islands.
  • C. LER
    LER is the vehicle registration code assigned to the German island municipality of Borkum.
  • D. LEAL
    LEAL is the ICAO airport code for Alicante–Elche Airport, the main international airport serving Spain’s Costa Blanca region.
  • E. Lela
    Lela is a feminine given name used in various cultures, often as a variant of Leila or Layla.
  • 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_69c69f21632481908bf83f6c6da897e3 completed March 27, 2026, 3:15 p.m.
NER Named-entity recognition batch_69c6f3d9d25c819087efc772b5b127fa completed March 27, 2026, 9:17 p.m.
NED1 Entity disambiguation (via context triple) batch_69c8346adb3081908f049d8dcd623215 completed March 28, 2026, 8:04 p.m.
NEDg Description generation batch_69c835904be081908fa9317eb5568d82 completed March 28, 2026, 8:09 p.m.
NED2 Entity disambiguation (via description) batch_69c83621b32c8190bd4b289b5f9f1764 completed March 28, 2026, 8:12 p.m.
Created at: March 27, 2026, 3:40 p.m.