Triple

T11697255
Position Surface form Disambiguated ID Type / Status
Subject Homburg E278027 entity
Predicate vehicleRegistrationCode P1173 FINISHED
Object HOM
HOM is the vehicle registration code for the German town of Homburg in the state of Saarland.
E941208 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: HOM | Statement: [Homburg, vehicleRegistrationCode, HOM]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: HOM
Context triple: [Homburg, vehicleRegistrationCode, HOM]
  • A. Homel
    Homel (also known as Gomel) is a major city in southeastern Belarus, situated on the Sozh River and serving as an important industrial, cultural, and historical center of the region.
  • B. HOL
    HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
  • C. Homowo
    Homowo is a major traditional harvest festival of the Ga people of Ghana, marked by rituals, drumming, dancing, and the symbolic “hooting at hunger.”
  • D. HM
    HM is an abbreviation commonly used as a formal title for a reigning queen or king, standing for "Her Majesty" or "His Majesty."
  • E. HM
    HM is a prefix used for classes and APIs in Apple's HomeKit framework, which enables communication and control of smart home accessories on iOS and other Apple platforms.
  • 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: HOM
Triple: [Homburg, vehicleRegistrationCode, HOM]
Generated description
HOM is the vehicle registration code for the German town of Homburg in the state of Saarland.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: HOM
Target entity description: HOM is the vehicle registration code for the German town of Homburg in the state of Saarland.
  • A. Homel
    Homel (also known as Gomel) is a major city in southeastern Belarus, situated on the Sozh River and serving as an important industrial, cultural, and historical center of the region.
  • B. HOL
    HOL is the commonly used abbreviation for the Hall of Languages, a historic academic building on the Syracuse University campus.
  • C. Homowo
    Homowo is a major traditional harvest festival of the Ga people of Ghana, marked by rituals, drumming, dancing, and the symbolic “hooting at hunger.”
  • D. HM
    HM is an abbreviation commonly used as a formal title for a reigning queen or king, standing for "Her Majesty" or "His Majesty."
  • E. HM
    HM is a prefix used for classes and APIs in Apple's HomeKit framework, which enables communication and control of smart home accessories on iOS and other Apple platforms.
  • 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_69d6aafe02d881909900d54ad7d4af84 completed April 8, 2026, 7:22 p.m.
NER Named-entity recognition batch_69d8a47cef60819088b7cc3a3a711e4c completed April 10, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69ef1471cba88190a7abdcbf4f579ea9 completed April 27, 2026, 7:46 a.m.
NEDg Description generation batch_69ef511f8f688190b2806d4e8ab16511 completed April 27, 2026, 12:05 p.m.
NED2 Entity disambiguation (via description) batch_69ef537efcc48190afffaa50f28940d8 completed April 27, 2026, 12:15 p.m.
Created at: April 8, 2026, 9:40 p.m.