Triple

T22939202
Position Surface form Disambiguated ID Type / Status
Subject Tilburg Reeshof railway station E569671 entity
Predicate stationCode P1289 FINISHED
Object Tlbr
Tlbr is the station code for Tilburg Reeshof, a suburban railway station in the city of Tilburg in the Netherlands.
 E1562582 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: Tlbr | Statement: [Tilburg Reeshof railway station, stationCode, Tlbr]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Tlbr
Context triple: [Tilburg Reeshof railway station, stationCode, Tlbr]
  • A. LTBR
    LTBR is the ICAO airport code for Bursa Yenişehir Airport, a public airport serving the Bursa region of Turkey.
  • B. LBR
    LBR is the National Rail station code for Llanbedr railway station in Gwynedd, Wales.
  • C. LBR
    LBR is the official FIFA trigramme used to represent the Liberia national football team in international competitions and records.
  • D. Tl
    Tl is the official station code used to identify Tiel railway station in the Netherlands.
  • E. TLB
    TLB is a popular paraphrased English version of the Bible aimed at making the text easily understandable in contemporary language.
  • 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: Tlbr
Triple: [Tilburg Reeshof railway station, stationCode, Tlbr]
Generated description
Tlbr is the station code for Tilburg Reeshof, a suburban railway station in the city of Tilburg in the Netherlands.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Tlbr
Target entity description: Tlbr is the station code for Tilburg Reeshof, a suburban railway station in the city of Tilburg in the Netherlands.
  • A. LTBR
    LTBR is the ICAO airport code for Bursa Yenişehir Airport, a public airport serving the Bursa region of Turkey.
  • B. LBR
    LBR is the official FIFA trigramme used to represent the Liberia national football team in international competitions and records.
  • C. LBR
    LBR is the National Rail station code for Llanbedr railway station in Gwynedd, Wales.
  • D. Tl
    Tl is the official station code used to identify Tiel railway station in the Netherlands.
  • E. TLB
    TLB is a popular paraphrased English version of the Bible aimed at making the text easily understandable in contemporary language.
  • 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_69e24590862c8190858f180ad302adab completed April 17, 2026, 2:37 p.m.
NER Named-entity recognition batch_69f181378660819083239986c846ec17 completed April 29, 2026, 3:55 a.m.
NED1 Entity disambiguation (via context triple) batch_6a0bc252cae48190bd7407dd38a21b19 completed May 19, 2026, 1:52 a.m.
NEDg Description generation batch_6a0bc455519c8190971c20082604846c completed May 19, 2026, 2 a.m.
NED2 Entity disambiguation (via description) batch_6a0bc533510c8190a286a7ebb1e7c3b7 completed May 19, 2026, 2:04 a.m.
Created at: April 17, 2026, 3:45 p.m.