Triple

T3501687
Position Surface form Disambiguated ID Type / Status
Subject State/Lake station E73981 entity
Predicate lineColorAssociation P34403 FINISHED
Object Brown E101694 NE FINISHED

How this triple was built (3 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: Brown | Statement: [State/Lake station, lineColorAssociation, Brown]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Brown
Context triple: [State/Lake station, lineColorAssociation, Brown]
  • A. Brown chosen
    Brown is a common English-language surname of Anglo-Saxon origin, typically derived from a nickname referring to hair color, complexion, or clothing.
  • B. Maroon
    Maroon refers to the descendants of escaped African slaves in the Americas who formed independent communities, notably in places like Suriname and Jamaica, preserving distinct African-derived cultures and traditions.
  • C. Gray
    Gray is the commonly used short form of the name Gray Davis, the former governor of California.
  • D. Gray
    Gray is a historic commune in eastern France known for its picturesque setting along the Saône River and its well-preserved old town.
  • E. Gray
    Gray is a common English surname of Anglo-Saxon origin, often associated with families from Britain and Ireland.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
PD Predicate disambiguation gpt-5-mini-2025-08-07
Target predicate: lineColorAssociation
Context triple: [State/Lake station, lineColorAssociation, Brown]
  • A. networkColorOfLine
    Indicates the color assigned to a specific line within a network (such as a transit or communication network).
  • B. lineLetterColorStandard
    Indicates the standard or default color assigned to the letter representation of a particular line.
  • C. trackColor
    Indicates the color associated with a given track in a context such as audio, video, or data sequencing.
  • D. mapColorLine chosen
    Indicates a relationship where a specific color is assigned to or associated with a particular line (such as a route, path, or boundary) on a map.
  • E. lineSymbol
    Indicates that one entity is used as a line-style or line-representation symbol for another entity.
  • F. None of above.

Provenance (4 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_69ad85cdb6e48190a335d412b9194ed8 completed March 8, 2026, 2:21 p.m.
NER Named-entity recognition batch_69adbbd5fbe8819091b61fa8df355f0c completed March 8, 2026, 6:11 p.m.
NED1 Entity disambiguation (via context triple) batch_69b373d88dc08190a8508f990b01cf03 completed March 13, 2026, 2:18 a.m.
PD Predicate disambiguation batch_69adae0cd8b0819099da300af09880da completed March 8, 2026, 5:12 p.m.
Created at: March 8, 2026, 3:18 p.m.