Triple

T8591878
Position Surface form Disambiguated ID Type / Status
Subject Laitila E203445 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object LAI
LAI is the vehicle registration code assigned to the Finnish town of Laitila.
 E745242 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: LAI | Statement: [Laitila, vehicleRegistrationCode, LAI]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LAI
Context triple: [Laitila, vehicleRegistrationCode, LAI]
  • A. LAU
    LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
  • B. LAJ
    LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
  • C. LATI
    LATI is the ICAO airport code for Tirana International Airport Nënë Tereza, the main international gateway to Albania.
  • D. LAC
    LAC refers to the Los Angeles Clippers, a professional NBA basketball team based in Los Angeles and a crosstown rival of the Los Angeles Lakers.
  • E. LAF
    The Lebanese Armed Forces (LAF) are the military institution of Lebanon, responsible for defending the country’s sovereignty, maintaining internal security, and operating under a delicate sectarian balance.
  • 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: LAI
Triple: [Laitila, vehicleRegistrationCode, LAI]
Generated description
LAI is the vehicle registration code assigned to the Finnish town of Laitila.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LAI
Target entity description: LAI is the vehicle registration code assigned to the Finnish town of Laitila.
  • A. LAU
    LAU is a private, internationally oriented university in Lebanon known for its American-style higher education and multiple campuses.
  • B. LAJ
    LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
  • C. LATI
    LATI is the ICAO airport code for Tirana International Airport Nënë Tereza, the main international gateway to Albania.
  • D. LAC
    LAC refers to the Los Angeles Clippers, a professional NBA basketball team based in Los Angeles and a crosstown rival of the Los Angeles Lakers.
  • E. LAF
    The Lebanese Armed Forces (LAF) are the military institution of Lebanon, responsible for defending the country’s sovereignty, maintaining internal security, and operating under a delicate sectarian balance.
  • 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_69ca832a7f108190b4e4f5648abf4aa2 completed March 30, 2026, 2:05 p.m.
NER Named-entity recognition batch_69cc466747b88190b752f78f361140cb completed March 31, 2026, 10:10 p.m.
NED1 Entity disambiguation (via context triple) batch_69cea8b584088190bc5b8b2785894d82 completed April 2, 2026, 5:34 p.m.
NEDg Description generation batch_69cea9cff1ec8190a0093fb42782341e completed April 2, 2026, 5:39 p.m.
NED2 Entity disambiguation (via description) batch_69ceaa9f7f8c8190965e86880ff141d5 completed April 2, 2026, 5:42 p.m.
Created at: March 30, 2026, 6:23 p.m.