Triple

T10742557
Position Surface form Disambiguated ID Type / Status
Subject Palau Reial E253363 entity
Predicate servedByLine P1293 FINISHED
Object L3
L3 is one of the main lines of the Barcelona Metro rapid transit system.
 E883863 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: L3 | Statement: [Palau Reial, servedByLine, L3]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: L3
Context triple: [Palau Reial, servedByLine, L3]
  • A. L3
    L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
  • B. L2
    L2 is the second Sun–Earth Lagrange point, a gravitationally stable location in space used by space telescopes such as the James Webb Space Telescope for observation.
  • C. L2
    L2 is the common shorthand for Ligue 2, the second tier of professional football in the French league system.
  • D. L2
    L2 is the commonly used designation for Line 2 of the Barcelona Metro, a rapid transit line serving several central and northern districts of the city.
  • E. L
    L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
  • 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: L3
Triple: [Palau Reial, servedByLine, L3]
Generated description
L3 is one of the main lines of the Barcelona Metro rapid transit system.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: L3
Target entity description: L3 is one of the main lines of the Barcelona Metro rapid transit system.
  • A. L3
    L3 is a particle physics experiment that operated at CERN’s Large Electron–Positron Collider, designed to study high-energy electron–positron collisions and probe the Standard Model.
  • B. L2
    L2 is the common shorthand for Ligue 2, the second tier of professional football in the French league system.
  • C. L2
    L2 is the second Sun–Earth Lagrange point, a gravitationally stable location in space used by space telescopes such as the James Webb Space Telescope for observation.
  • D. L2
    L2 is the commonly used designation for Line 2 of the Barcelona Metro, a rapid transit line serving several central and northern districts of the city.
  • E. L
    L is the enigmatic, emotionally complex protagonist of Hanne Ørstavik’s novel "Love," whose inner life and perspective drive the story’s exploration of isolation and longing.
  • 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_69d6aa5e51e8819095f06881cecf152e completed April 8, 2026, 7:19 p.m.
NER Named-entity recognition batch_69d710456ec88190ad8aff8804d13aa9 completed April 9, 2026, 2:34 a.m.
NED1 Entity disambiguation (via context triple) batch_69de22fc13b0819098caf88328397053 completed April 14, 2026, 11:20 a.m.
NEDg Description generation batch_69de271e2698819093bba748a0a0db5d completed April 14, 2026, 11:38 a.m.
NED2 Entity disambiguation (via description) batch_69de2cdd79608190bad8045939556bc7 completed April 14, 2026, 12:02 p.m.
Created at: April 8, 2026, 9:15 p.m.