Triple

T10741597
Position Surface form Disambiguated ID Type / Status
Subject Luas E253338 entity
Predicate hasStation P35 FINISHED
Object Red Cow
Red Cow is a major Luas light rail stop and park-and-ride interchange on the outskirts of Dublin, Ireland.
 E883833 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: Red Cow | Statement: [Luas, hasStation, Red Cow]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Red Cow
Context triple: [Luas, hasStation, Red Cow]
  • A. The Cow
    The Cow is the English title of Surah Al-Baqarah, the Quran’s longest chapter, which covers core themes of faith, law, guidance, and the relationship between God and humanity.
  • B. The Cow
    The Cow is a landmark 1969 Iranian drama film directed by Dariush Mehrjui that is widely credited with helping launch the Iranian New Wave.
  • C. Mad Cows
    Mad Cows is a 1999 British comedy film about a chaotic series of misadventures involving a young mother entangled in crime and bureaucracy.
  • D. The Cattle
    The Cattle is the English title of Surah Al-An'am, the sixth chapter of the Qur’an, which focuses on themes of monotheism, divine guidance, and the refutation of idolatry.
  • E. Cattle Call
    "Cattle Call" is a classic American country and cowboy song, best known through Eddy Arnold’s popular 1955 recording.
  • 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: Red Cow
Triple: [Luas, hasStation, Red Cow]
Generated description
Red Cow is a major Luas light rail stop and park-and-ride interchange on the outskirts of Dublin, Ireland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Red Cow
Target entity description: Red Cow is a major Luas light rail stop and park-and-ride interchange on the outskirts of Dublin, Ireland.
  • A. The Cow
    The Cow is the English title of Surah Al-Baqarah, the Quran’s longest chapter, which covers core themes of faith, law, guidance, and the relationship between God and humanity.
  • B. The Cow
    The Cow is a landmark 1969 Iranian drama film directed by Dariush Mehrjui that is widely credited with helping launch the Iranian New Wave.
  • C. Mad Cows
    Mad Cows is a 1999 British comedy film about a chaotic series of misadventures involving a young mother entangled in crime and bureaucracy.
  • D. The Cattle
    The Cattle is the English title of Surah Al-An'am, the sixth chapter of the Qur’an, which focuses on themes of monotheism, divine guidance, and the refutation of idolatry.
  • E. Cattle Call
    "Cattle Call" is a classic American country and cowboy song, best known through Eddy Arnold’s popular 1955 recording.
  • 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_69d7104446288190800253f8b652f710 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.