Triple

T12112618
Position Surface form Disambiguated ID Type / Status
Subject Guadalupe station E288469 entity
Predicate hasStationCode P1289 FINISHED
Object GU
GU is the station code used to identify Guadalupe station within the railway network.
 E965039 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: GU | Statement: [Guadalupe station, hasStationCode, GU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: GU
Context triple: [Guadalupe station, hasStationCode, GU]
  • A. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • B. GU
    GU is an alternative name or abbreviation for the Gated Recurrent Unit, a type of recurrent neural network architecture used in deep learning for sequence modeling tasks.
  • C. GU
    GU is a United Kingdom postcode area covering Guildford and surrounding parts of Surrey and nearby counties.
  • D. GN
    GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
  • E. GD
    GD is the stock ticker symbol for General Dynamics, a major American aerospace and defense corporation.
  • 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: GU
Triple: [Guadalupe station, hasStationCode, GU]
Generated description
GU is the station code used to identify Guadalupe station within the railway network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: GU
Target entity description: GU is the station code used to identify Guadalupe station within the railway network.
  • A. GU
    GU is the two-letter ISO 3166 country code assigned to Guam, an unincorporated territory of the United States in the western Pacific Ocean.
  • B. GU
    GU is a United Kingdom postcode area covering Guildford and surrounding parts of Surrey and nearby counties.
  • C. GU
    GU is an alternative name or abbreviation for the Gated Recurrent Unit, a type of recurrent neural network architecture used in deep learning for sequence modeling tasks.
  • D. GN
    GN is a fast, meta-build system tool used primarily by the Chromium project to generate build files for Ninja.
  • E. GD
    GD is the stock ticker symbol for General Dynamics, a major American aerospace and defense corporation.
  • 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_69d6ab4a5c448190a110d1273314b21a completed April 8, 2026, 7:23 p.m.
NER Named-entity recognition batch_69d9156814148190b47d63a89fcab17c completed April 10, 2026, 3:21 p.m.
NED1 Entity disambiguation (via context triple) batch_69f5f67d58d08190be45fb49f0084b49 completed May 2, 2026, 1:05 p.m.
NEDg Description generation batch_69f600b6769481909d0308c8f77b2ef3 completed May 2, 2026, 1:48 p.m.
NED2 Entity disambiguation (via description) batch_69f601e7f3b0819098a2245b9f9316b9 completed May 2, 2026, 1:53 p.m.
Created at: April 8, 2026, 9:49 p.m.