Triple

T14783060
Position Surface form Disambiguated ID Type / Status
Subject Port of Helsingborg E347439 entity
Predicate hasUNLocode P1492 FINISHED
Object SEHEL
SEHEL is the UN/LOCODE designation for the Port of Helsingborg in Sweden, used in international trade and transport documentation.
 E1119717 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: SEHEL | Statement: [Port of Helsingborg, hasUNLocode, SEHEL]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: SEHEL
Context triple: [Port of Helsingborg, hasUNLocode, SEHEL]
  • A. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • B. Onhel
    Onhel is a music producer and audio engineer known for his work on major hip-hop projects, including Lil Wayne’s album "Tha Carter V."
  • C. سيهات
    سيهات هي مدينة ساحلية تقع على الخليج العربي في المنطقة الشرقية من المملكة العربية السعودية وتشتهر بصيد الأسماك والنشاطات البحرية.
  • D. SEBL
    SEBL was the stock ticker symbol for Siebel Systems, a prominent customer relationship management (CRM) software company later acquired by Oracle.
  • E. Sehar
    Sehar is a 2005 Indian crime drama film acclaimed for its realistic portrayal of the Uttar Pradesh police force and the criminal underworld.
  • 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: SEHEL
Triple: [Port of Helsingborg, hasUNLocode, SEHEL]
Generated description
SEHEL is the UN/LOCODE designation for the Port of Helsingborg in Sweden, used in international trade and transport documentation.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: SEHEL
Target entity description: SEHEL is the UN/LOCODE designation for the Port of Helsingborg in Sweden, used in international trade and transport documentation.
  • A. SEEL
    SEEL is the abbreviation for the Space Environmental Effects Laboratory, a facility focused on studying how the space environment impacts materials and systems.
  • B. Onhel
    Onhel is a music producer and audio engineer known for his work on major hip-hop projects, including Lil Wayne’s album "Tha Carter V."
  • C. سيهات
    سيهات هي مدينة ساحلية تقع على الخليج العربي في المنطقة الشرقية من المملكة العربية السعودية وتشتهر بصيد الأسماك والنشاطات البحرية.
  • D. SEBL
    SEBL was the stock ticker symbol for Siebel Systems, a prominent customer relationship management (CRM) software company later acquired by Oracle.
  • E. Sehar
    Sehar is a 2005 Indian crime drama film acclaimed for its realistic portrayal of the Uttar Pradesh police force and the criminal underworld.
  • 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_69d822e9b9e08190bedcc31a163fda82 completed April 9, 2026, 10:06 p.m.
NER Named-entity recognition batch_69deca9de3f48190b7706925e2947cf5 completed April 14, 2026, 11:15 p.m.
NED1 Entity disambiguation (via context triple) batch_69fe0d02e28081909a11d6e6fdb8d28c completed May 8, 2026, 4:19 p.m.
NEDg Description generation batch_69fe19e2e0288190830e073eeefcdc24 completed May 8, 2026, 5:14 p.m.
NED2 Entity disambiguation (via description) batch_69fe1a89d4d08190a2be8b4b0bc5a472 completed May 8, 2026, 5:16 p.m.
Created at: April 10, 2026, 1:31 a.m.