Triple

T12090634
Position Surface form Disambiguated ID Type / Status
Subject Morningside Heights E287930 entity
Predicate servedByBusRoute P14525 FINISHED
Object M4
M4 is a New York City bus route that runs through Manhattan, connecting key neighborhoods including Morningside Heights with Midtown and downtown areas.
 E962532 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: M4 | Statement: [Morningside Heights, servedByBusRoute, M4]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: M4
Context triple: [Morningside Heights, servedByBusRoute, M4]
  • A. M4
    M4 is a general-purpose macro processing language and preprocessor commonly used in Unix-like build systems and tools such as GNU Autoconf.
  • B. M4
    M4 is one of the lines of the Bucharest Metro rapid transit system, serving several northern and northwestern districts of Romania’s capital.
  • C. M4
    M4 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across Lake Geneva.
  • D. M4
    M4 is a driverless metro line in the Copenhagen Metro system that serves key waterfront and urban development areas of the city.
  • E. M4
    M4 is one of the main lines of the Paris Métro, running north–south across the city and serving several central and historically significant stations.
  • 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: M4
Triple: [Morningside Heights, servedByBusRoute, M4]
Generated description
M4 is a New York City bus route that runs through Manhattan, connecting key neighborhoods including Morningside Heights with Midtown and downtown areas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: M4
Target entity description: M4 is a New York City bus route that runs through Manhattan, connecting key neighborhoods including Morningside Heights with Midtown and downtown areas.
  • A. M4
    M4 is one of the main lines of the Paris Métro, running north–south across the city and serving several central and historically significant stations.
  • B. M4
    M4 is one of the lines of the Bucharest Metro rapid transit system, serving several northern and northwestern districts of Romania’s capital.
  • C. M4
    M4 is a driverless metro line in the Copenhagen Metro system that serves key waterfront and urban development areas of the city.
  • D. M4
    M4 is a boat line that operates as part of Geneva’s public transport network, providing passenger service across Lake Geneva.
  • E. M4
    M4 is a major British motorway that runs between London and South Wales, serving as a key route for traffic to and from the west of England.
  • 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_69d6ab4964708190850585628b287b0c completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9151797988190b0d007ea806bcf02 completed April 10, 2026, 3:19 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f66b2eb48190bae469d1dd82b119 completed May 2, 2026, 1:04 p.m.
NEDg Description generation batch_69f5fd79da748190b3f0dd7d7a46314d completed May 2, 2026, 1:34 p.m.
NED2 Entity disambiguation (via description) batch_69f5feeeeb2081908191b1c2d1c2fbfd completed May 2, 2026, 1:41 p.m.
Created at: April 8, 2026, 9:48 p.m.