Triple

T3346284
Position Surface form Disambiguated ID Type / Status
Subject Valencia Airport E70381 entity
Predicate nearbyTown P3883 FINISHED
Object Manises
Manises is a town in Spain’s Valencian Community, known for its historic ceramics industry and proximity to Valencia.
E350369 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: Manises | Statement: [Valencia Airport, nearbyTown, Manises]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Manises
Context triple: [Valencia Airport, nearbyTown, Manises]
  • A. Mariveles
    Mariveles is a coastal municipality at the southern tip of the Bataan Peninsula in the Philippines, known for its deep-water port, industrial zones, and role in World War II history.
  • B. Masbateño
    Masbateño is a Central Philippine Bisayan language spoken primarily on Masbate Island in the Philippines.
  • C. Malpaso
    Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
  • D. Nueva Gerona
    Nueva Gerona is the main urban center and administrative hub of Cuba’s Isla de la Juventud, known for its port, local commerce, and role in regional governance.
  • E. Surigaonon
    Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
  • 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: Manises
Triple: [Valencia Airport, nearbyTown, Manises]
Generated description
Manises is a town in Spain’s Valencian Community, known for its historic ceramics industry and proximity to Valencia.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Manises
Target entity description: Manises is a town in Spain’s Valencian Community, known for its historic ceramics industry and proximity to Valencia.
  • A. Mariveles
    Mariveles is a coastal municipality at the southern tip of the Bataan Peninsula in the Philippines, known for its deep-water port, industrial zones, and role in World War II history.
  • B. Masbateño
    Masbateño is a Central Philippine Bisayan language spoken primarily on Masbate Island in the Philippines.
  • C. Malpaso
    Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
  • D. Nueva Gerona
    Nueva Gerona is the main urban center and administrative hub of Cuba’s Isla de la Juventud, known for its port, local commerce, and role in regional governance.
  • E. Surigaonon
    Surigaonon is a Visayan language spoken primarily in the Caraga region of northeastern Mindanao in the Philippines.
  • 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_69ad85a405e48190b6e68de7cf9f319e completed March 8, 2026, 2:20 p.m.
NER Named-entity recognition batch_69adb1f4ff888190bf14b9b7fbe9bcee completed March 8, 2026, 5:29 p.m.
NED1 Entity disambiguation (via context triple) batch_69b32522cbc88190b965087a580d7acf completed March 12, 2026, 8:42 p.m.
NEDg Description generation batch_69b325a0de7c8190a33ae611b8450b5a completed March 12, 2026, 8:44 p.m.
NED2 Entity disambiguation (via description) batch_69b326862e848190bf1bea74b6ab0b36 completed March 12, 2026, 8:48 p.m.
Created at: March 8, 2026, 3:12 p.m.