Triple

T12382549
Position Surface form Disambiguated ID Type / Status
Subject Timeless E295778 entity
Predicate hasTrack P3284 FINISHED
Object LCND
LCND is a track by the American hip-hop collective Timeless, showcasing their style within the contemporary rap scene.
 E976748 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: LCND | Statement: [Timeless, hasTrack, LCND]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: LCND
Context triple: [Timeless, hasTrack, LCND]
  • A. LCN
    LCN is the National Rail station code for Lincoln railway station in Lincoln, England.
  • B. LCN
    LCN, short for La Cosa Nostra, is a notorious Italian-American organized crime syndicate known for its hierarchical structure, code of silence, and influence over various illegal enterprises in the United States.
  • C. LCNC
    LCNC is the ICAO airport code assigned to Nicosia International Airport in Cyprus.
  • D. CNDLC
    CNDLC is the UN/LOCODE identifier for the Port of Dalian, a major seaport in northeastern China.
  • E. LCEN
    LCEN is the ICAO airport code for Ercan International Airport, the main air gateway to Northern Cyprus.
  • 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: LCND
Triple: [Timeless, hasTrack, LCND]
Generated description
LCND is a track by the American hip-hop collective Timeless, showcasing their style within the contemporary rap scene.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: LCND
Target entity description: LCND is a track by the American hip-hop collective Timeless, showcasing their style within the contemporary rap scene.
  • A. LCN
    LCN is the National Rail station code for Lincoln railway station in Lincoln, England.
  • B. LCN
    LCN, short for La Cosa Nostra, is a notorious Italian-American organized crime syndicate known for its hierarchical structure, code of silence, and influence over various illegal enterprises in the United States.
  • C. LCNC
    LCNC is the ICAO airport code assigned to Nicosia International Airport in Cyprus.
  • D. CNDLC
    CNDLC is the UN/LOCODE identifier for the Port of Dalian, a major seaport in northeastern China.
  • E. LCEN
    LCEN is the ICAO airport code for Ercan International Airport, the main air gateway to Northern Cyprus.
  • 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_69d6ad9e653c8190b1473c860ee53dae completed April 8, 2026, 7:33 p.m.
NER Named-entity recognition batch_69d93fbb3a2481908c2fcb5e6488eb3c completed April 10, 2026, 6:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f62ac5b46c81908d419e09f5629c37 completed May 2, 2026, 4:48 p.m.
NEDg Description generation batch_69f62c586ee8819082421b87572d5f1b completed May 2, 2026, 4:54 p.m.
NED2 Entity disambiguation (via description) batch_69f62caa8dbc8190ac233f4913159746 completed May 2, 2026, 4:56 p.m.
Created at: April 8, 2026, 9:54 p.m.