Triple

T1743534
Position Surface form Disambiguated ID Type / Status
Subject Shanghai South Railway Station E38284 entity
Predicate hasStationCode P1289 FINISHED
Object SHH
SHH is the railway station code used to identify Shanghai South Railway Station in China’s rail network.
E193132 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: SHH | Statement: [Shanghai South Railway Station, hasStationCode, SHH]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: SHH
Context triple: [Shanghai South Railway Station, hasStationCode, SHH]
  • A. Hish
    Hish was a field corps branch of the Haganah, the main Jewish paramilitary organization in Mandatory Palestine before the establishment of the State of Israel.
  • B. CHH
    CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
  • C. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • D. SHASS
    SHASS is the abbreviated name commonly used for the School of Humanities, Arts, and Social Sciences at academic institutions.
  • E. Shuar
    Shuar is an indigenous language of the Jivaroan family spoken by the Shuar people primarily in the Amazonian regions of Ecuador and Peru.
  • 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: SHH
Triple: [Shanghai South Railway Station, hasStationCode, SHH]
Generated description
SHH is the railway station code used to identify Shanghai South Railway Station in China’s rail network.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: SHH
Target entity description: SHH is the railway station code used to identify Shanghai South Railway Station in China’s rail network.
  • A. Hish
    Hish was a field corps branch of the Haganah, the main Jewish paramilitary organization in Mandatory Palestine before the establishment of the State of Israel.
  • B. CHH
    CHH is the vehicle registration code used on license plates for the Mexican state of Chihuahua.
  • C. HH
    HH is the vehicle registration code used on license plates for the German city-state of Hamburg.
  • D. SHASS
    SHASS is the abbreviated name commonly used for the School of Humanities, Arts, and Social Sciences at academic institutions.
  • E. Shuar
    Shuar is an indigenous language of the Jivaroan family spoken by the Shuar people primarily in the Amazonian regions of Ecuador and Peru.
  • 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_69a8862b01a48190ab47209063af82d9 completed March 4, 2026, 7:21 p.m.
NER Named-entity recognition batch_69aa63c836d48190bd44ea24977aba2d completed March 6, 2026, 5:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ad8b0ab7008190a2fafe1c8ac55ac4 completed March 8, 2026, 2:43 p.m.
NEDg Description generation batch_69ad957f64c48190862a701a94098bbf completed March 8, 2026, 3:27 p.m.
NED2 Entity disambiguation (via description) batch_69ad97b974708190adfffebee41a6fcd completed March 8, 2026, 3:37 p.m.
Created at: March 4, 2026, 7:31 p.m.