Triple

T15313950
Position Surface form Disambiguated ID Type / Status
Subject Dallas Water Utilities E366105 entity
Predicate alsoKnownAs P39 FINISHED
Object DWU
DWU is the municipal water and wastewater utility department serving the city of Dallas, Texas.
 E1150792 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: DWU | Statement: [Dallas Water Utilities, alsoKnownAs, DWU]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: DWU
Context triple: [Dallas Water Utilities, alsoKnownAs, DWU]
  • A. DW
    DW is the abbreviation for Deutsche Werft AG, a former German shipbuilding company based in Hamburg.
  • B. DW
    DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
  • C. DW
    DW is the vehicle registration code used on license plates for the Sächsische Schweiz-Osterzgebirge district in the German state of Saxony.
  • D. DUS
    DUS is the three-letter IATA code for Düsseldorf Airport, a major international airport in western Germany.
  • E. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • 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: DWU
Triple: [Dallas Water Utilities, alsoKnownAs, DWU]
Generated description
DWU is the municipal water and wastewater utility department serving the city of Dallas, Texas.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: DWU
Target entity description: DWU is the municipal water and wastewater utility department serving the city of Dallas, Texas.
  • A. DW
    DW is the abbreviation for Deutsche Werft AG, a former German shipbuilding company based in Hamburg.
  • B. DW
    DW is the commonly used abbreviation for Daniel Wellington, a Swedish watch and accessories brand known for its minimalist, classic designs.
  • C. DW
    DW is the vehicle registration code used on license plates for the Sächsische Schweiz-Osterzgebirge district in the German state of Saxony.
  • D. DUS
    DUS is the three-letter IATA code for Düsseldorf Airport, a major international airport in western Germany.
  • E. WU
    WU is the stock ticker symbol for Western Union, a global financial services company best known for its money transfer and payment services.
  • 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_69d85a113ee881908e297a1d38dd79fa completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03dd050108190a584543cb93943a4 completed April 16, 2026, 1:39 a.m.
NED1 Entity disambiguation (via context triple) batch_69fef8a3da3881909b50cfbec0543adc completed May 9, 2026, 9:04 a.m.
NEDg Description generation batch_69fefdb82b2081908084a12a58ad3477 completed May 9, 2026, 9:26 a.m.
NED2 Entity disambiguation (via description) batch_69fefe6c42708190bd893885fc5bc88e completed May 9, 2026, 9:29 a.m.
Created at: April 10, 2026, 3:16 a.m.