Triple

T10942421
Position Surface form Disambiguated ID Type / Status
Subject Hillsdale station E258505 entity
Predicate hasStationCode P1289 FINISHED
Object HDL
HDL is the station code assigned to Hillsdale station, a commuter rail stop in California.
 E895422 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: HDL | Statement: [Hillsdale station, hasStationCode, HDL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: HDL
Context triple: [Hillsdale station, hasStationCode, HDL]
  • A. HDX
    HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
  • B. Ldl
    Ldl is the official station code for Leiden Lammenschans railway station in the Netherlands.
  • C. HDI
    The HDI is a composite statistic used by the United Nations to measure and compare countries’ overall human development based on health, education, and standard of living.
  • D. HCD
    HCD is the California state agency responsible for housing policy, affordable housing programs, and community development initiatives.
  • E. HCD
    HCD is the common abbreviation for HC Davos, a professional ice hockey club based in Davos, Switzerland.
  • 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: HDL
Triple: [Hillsdale station, hasStationCode, HDL]
Generated description
HDL is the station code assigned to Hillsdale station, a commuter rail stop in California.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: HDL
Target entity description: HDL is the station code assigned to Hillsdale station, a commuter rail stop in California.
  • A. HDX
    HDX is an open humanitarian data platform that enables organizations to share, find, and use data for crisis preparedness and response.
  • B. Ldl
    Ldl is the official station code for Leiden Lammenschans railway station in the Netherlands.
  • C. HDI
    The HDI is a composite statistic used by the United Nations to measure and compare countries’ overall human development based on health, education, and standard of living.
  • D. HCD
    HCD is the California state agency responsible for housing policy, affordable housing programs, and community development initiatives.
  • E. HCD
    HCD is the common abbreviation for HC Davos, a professional ice hockey club based in Davos, Switzerland.
  • 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_69d6aa8769b4819082bfe5e61b9017f0 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d770c33a7c8190b3347944f68ee431 completed April 9, 2026, 9:26 a.m.
NED1 Entity disambiguation (via context triple) batch_69e23c1ed4f081909ac5731dac325466 completed April 17, 2026, 1:56 p.m.
NEDg Description generation batch_69e24542b4f081909c97621f04da8ecc completed April 17, 2026, 2:35 p.m.
NED2 Entity disambiguation (via description) batch_69e248f7f96481909fa6e6cd07891566 completed April 17, 2026, 2:51 p.m.
Created at: April 8, 2026, 9:23 p.m.