Triple

T12816350
Position Surface form Disambiguated ID Type / Status
Subject European Union NUTS-2 region ES52 (Comunitat Valenciana) E306411 entity
Predicate NUTSCode P2415 FINISHED
Object ES52
ES52 is the NUTS-2 statistical region corresponding to the Spanish autonomous community of the Valencian Community on the Mediterranean coast.
 E1004250 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: ES52 | Statement: [European Union NUTS-2 region ES52 (Comunitat Valenciana), NUTSCode, ES52]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: ES52
Context triple: [European Union NUTS-2 region ES52 (Comunitat Valenciana), NUTSCode, ES52]
  • A. E52
    E52 is a Nokia Eseries mobile phone model known for its slim design, long battery life, and business-oriented features.
  • B. S52
    S52 is a bus service route that provides public transportation access to the village of Grasmere.
  • C. E50
    E50 is a major trans-European road corridor that spans multiple countries, facilitating long-distance east–west travel and trade across the continent.
  • D. DS526
    DS526 is a World Trade Organization dispute case concerning Qatar’s trade-related measures affecting goods and services originating from the United Arab Emirates.
  • E. E5
    E5 is the IATA airline designator assigned to Air Arabia Egypt, a low-cost carrier based in Egypt.
  • 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: ES52
Triple: [European Union NUTS-2 region ES52 (Comunitat Valenciana), NUTSCode, ES52]
Generated description
ES52 is the NUTS-2 statistical region corresponding to the Spanish autonomous community of the Valencian Community on the Mediterranean coast.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: ES52
Target entity description: ES52 is the NUTS-2 statistical region corresponding to the Spanish autonomous community of the Valencian Community on the Mediterranean coast.
  • A. E52
    E52 is a Nokia Eseries mobile phone model known for its slim design, long battery life, and business-oriented features.
  • B. S52
    S52 is a bus service route that provides public transportation access to the village of Grasmere.
  • C. E50
    E50 is a major trans-European road corridor that spans multiple countries, facilitating long-distance east–west travel and trade across the continent.
  • D. DS526
    DS526 is a World Trade Organization dispute case concerning Qatar’s trade-related measures affecting goods and services originating from the United Arab Emirates.
  • E. E5
    E5 is the IATA airline designator assigned to Air Arabia Egypt, a low-cost carrier based in Egypt.
  • 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_69d7bdf46c448190b1faa55aaacb6317 completed April 9, 2026, 2:55 p.m.
NER Named-entity recognition batch_69d96e9beb30819097c256a5aab9a4c8 completed April 10, 2026, 9:41 p.m.
NED1 Entity disambiguation (via context triple) batch_69f68ecee33c8190a6bf045731bb9326 completed May 2, 2026, 11:54 p.m.
NEDg Description generation batch_69f691341d0081909ca3b281ee64b42b completed May 3, 2026, 12:05 a.m.
NED2 Entity disambiguation (via description) batch_69f692361c3c81909078a19be1a86231 completed May 3, 2026, 12:09 a.m.
Created at: April 9, 2026, 5:31 p.m.