Triple

T2485725
Position Surface form Disambiguated ID Type / Status
Subject Zaragoza E55920 entity
Predicate otherRiver P165 FINISHED
Object Huerva
The Huerva is a river in northeastern Spain that flows through the province of Zaragoza before joining the Ebro River.
 E271145 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: Huerva | Statement: [Zaragoza, otherRiver, Huerva]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Huerva
Context triple: [Zaragoza, otherRiver, Huerva]
  • A. Caleruega
    Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
  • B. Mati
    Mati is a coastal city in the Davao Region of the Philippines known for its beaches, surfing spots, and laid-back atmosphere.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Cogua
    Cogua is a municipality in the Cundinamarca Department of Colombia, located on the Bogotá savanna north of the capital.
  • E. Yaxartes
    Yaxartes is the ancient name, used by classical Greek and Roman sources, for the Syr Darya River of Central Asia.
  • 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: Huerva
Triple: [Zaragoza, otherRiver, Huerva]
Generated description
The Huerva is a river in northeastern Spain that flows through the province of Zaragoza before joining the Ebro River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Huerva
Target entity description: The Huerva is a river in northeastern Spain that flows through the province of Zaragoza before joining the Ebro River.
  • A. Caleruega
    Caleruega is a small town in the province of Burgos, Spain, best known as the birthplace of Saint Dominic, founder of the Dominican Order.
  • B. Mati
    Mati is a coastal city in the Davao Region of the Philippines known for its beaches, surfing spots, and laid-back atmosphere.
  • C. Moura
    Moura is a historic town in Portugal’s Alentejo region, known for its whitewashed architecture, olive oil production, and proximity to the Alqueva reservoir.
  • D. Cogua
    Cogua is a municipality in the Cundinamarca Department of Colombia, located on the Bogotá savanna north of the capital.
  • E. Yaxartes
    Yaxartes is the ancient name, used by classical Greek and Roman sources, for the Syr Darya River of Central Asia.
  • 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_69ab49e670a88190b928e08302381710 completed March 6, 2026, 9:40 p.m.
NER Named-entity recognition batch_69abd17705488190b90b1aa66dd25972 completed March 7, 2026, 7:19 a.m.
NED1 Entity disambiguation (via context triple) batch_69af17ba433481908eccda5c6c6246be completed March 9, 2026, 6:55 p.m.
NEDg Description generation batch_69af1bbf545081908e1e51b5c7e4a196 completed March 9, 2026, 7:13 p.m.
NED2 Entity disambiguation (via description) batch_69af1c9c35648190bdeab34ce4032d26 completed March 9, 2026, 7:16 p.m.
Created at: March 6, 2026, 9:45 p.m.