Triple

T2720867
Position Surface form Disambiguated ID Type / Status
Subject Oyster card E60075 entity
Predicate brandName P1500 FINISHED
Object Oyster
Oyster is a contactless smartcard used for paying fares on public transport in London.
 E293568 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: Oyster | Statement: [Oyster card, brandName, Oyster]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Oyster
Context triple: [Oyster card, brandName, Oyster]
  • A. Mejillones
    Mejillones is a coastal Chilean port city on the Pacific Ocean, known for its fishing industry and role in regional maritime trade.
  • B. Dungeness crab
    The Dungeness crab is a large, commercially important crab species native to the Pacific coast of North America, prized for its sweet, tender meat.
  • C. Ika
    Ika is a Sanskrit-derived word meaning “one” or “unity,” used in the Indonesian national motto “Bhinneka Tunggal Ika” to express the idea of oneness amid diversity.
  • D. Pomfret
    Pomfret is a small, historic town in northeastern Connecticut known for its rural character, scenic landscapes, and prestigious boarding schools.
  • E. Tonna
    Tonna is a village and community in Neath Port Talbot, South Wales, known for its residential character and proximity to the town of Neath.
  • 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: Oyster
Triple: [Oyster card, brandName, Oyster]
Generated description
Oyster is a contactless smartcard used for paying fares on public transport in London.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Oyster
Target entity description: Oyster is a contactless smartcard used for paying fares on public transport in London.
  • A. Mejillones
    Mejillones is a coastal Chilean port city on the Pacific Ocean, known for its fishing industry and role in regional maritime trade.
  • B. Dungeness crab
    The Dungeness crab is a large, commercially important crab species native to the Pacific coast of North America, prized for its sweet, tender meat.
  • C. Ika
    Ika is a Sanskrit-derived word meaning “one” or “unity,” used in the Indonesian national motto “Bhinneka Tunggal Ika” to express the idea of oneness amid diversity.
  • D. Pomfret
    Pomfret is a small, historic town in northeastern Connecticut known for its rural character, scenic landscapes, and prestigious boarding schools.
  • E. Tonna
    Tonna is a village and community in Neath Port Talbot, South Wales, known for its residential character and proximity to the town of Neath.
  • 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_69ab4b746d248190958e052045c09255 completed March 6, 2026, 9:47 p.m.
NER Named-entity recognition batch_69abdab1cb808190b0789c76bc9cb090 completed March 7, 2026, 7:58 a.m.
NED1 Entity disambiguation (via context triple) batch_69afb6914f70819099482893d026f34b completed March 10, 2026, 6:13 a.m.
NEDg Description generation batch_69afb726182081909570e4cb7a364e4d completed March 10, 2026, 6:16 a.m.
NED2 Entity disambiguation (via description) batch_69afb78f9d08819087d6f31fe1e4e61c completed March 10, 2026, 6:17 a.m.
Created at: March 6, 2026, 9:55 p.m.