Triple

T15245463
Position Surface form Disambiguated ID Type / Status
Subject Collevecchio E364367 entity
Predicate hasRegionCode P3446 FINISHED
Object LAZ
LAZ is the regional code for Lazio, a central Italian region that includes Rome and its surrounding areas.
 E1145583 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: LAZ | Statement: [Collevecchio, hasRegionCode, LAZ]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LAZ
Context triple: [Collevecchio, hasRegionCode, LAZ]
  • A. LAZ
    LAZ is the station code for San Lázaro, a Mexico City Metro station serving Line 1 and Line B near the city’s eastern transport hubs.
  • B. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • C. LAJ
    LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
  • D. Lazi
    Lazi is a coastal municipality on the southeastern side of Siquijor Island in the Philippines, known for its historic church, natural springs, and waterfalls.
  • E. LZ
    LZ is the stock ticker symbol for The Lubrizol Corporation, a specialty chemicals company known for its lubricant additives and advanced materials.
  • 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: LAZ
Triple: [Collevecchio, hasRegionCode, LAZ]
Generated description
LAZ is the regional code for Lazio, a central Italian region that includes Rome and its surrounding areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LAZ
Target entity description: LAZ is the regional code for Lazio, a central Italian region that includes Rome and its surrounding areas.
  • A. LAZ
    LAZ is the station code for San Lázaro, a Mexico City Metro station serving Line 1 and Line B near the city’s eastern transport hubs.
  • B. Laz
    Laz is a South Caucasian (Kartvelian) language traditionally spoken by the Laz people along the southeastern Black Sea coast, particularly in northeastern Turkey and parts of Georgia.
  • C. LAJ
    LAJ is the station code for La Junta station, an Amtrak railroad stop in La Junta, Colorado, serving long-distance passenger trains.
  • D. Lazi
    Lazi is a coastal municipality on the southeastern side of Siquijor Island in the Philippines, known for its historic church, natural springs, and waterfalls.
  • E. LZ
    LZ is the stock ticker symbol for The Lubrizol Corporation, a specialty chemicals company known for its lubricant additives and advanced materials.
  • 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_69d85a0dde7481908fc64d1e82d5d20d completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e007f306f08190be448b215d6c9b6c completed April 15, 2026, 9:49 p.m.
NED1 Entity disambiguation (via context triple) batch_69fedd461cf08190a506aac2f0cec83a completed May 9, 2026, 7:07 a.m.
NEDg Description generation batch_69fedf6ee3f081909553078cd3e9d243 completed May 9, 2026, 7:17 a.m.
NED2 Entity disambiguation (via description) batch_69fee0016a088190ad87268e035f677e completed May 9, 2026, 7:19 a.m.
Created at: April 10, 2026, 3:13 a.m.