Triple

T10804517
Position Surface form Disambiguated ID Type / Status
Subject Alt Penedès E254928 entity
Predicate hasMunicipality P847 FINISHED
Object Gelida
Gelida is a municipality in the Alt Penedès comarca of Catalonia, Spain, known for its hillside setting and historic funicular railway.
 E886663 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: Gelida | Statement: [Alt Penedès, hasMunicipality, Gelida]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Gelida
Context triple: [Alt Penedès, hasMunicipality, Gelida]
  • A. Chionê
    Chionê is a figure from Greek mythology, often associated with snow and winter and appearing in various mythic traditions under slightly different name forms.
  • B. Gelo
    Gelo is a film featuring Spanish actress Ivana Baquero in a prominent role.
  • C. Givlaari
    Givlaari is an RNA interference-based therapy used to treat acute hepatic porphyria by reducing the production of toxic heme intermediates in the liver.
  • D. Gorely
    Gorely is an active stratovolcano complex on Russia’s Kamchatka Peninsula, known for its multiple craters, frequent eruptions, and striking acidic crater lakes.
  • E. Frosta
    Frosta is a rural municipality and peninsula in Trøndelag county, Norway, known for its fertile farmland and historical significance as a medieval assembly site.
  • 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: Gelida
Triple: [Alt Penedès, hasMunicipality, Gelida]
Generated description
Gelida is a municipality in the Alt Penedès comarca of Catalonia, Spain, known for its hillside setting and historic funicular railway.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Gelida
Target entity description: Gelida is a municipality in the Alt Penedès comarca of Catalonia, Spain, known for its hillside setting and historic funicular railway.
  • A. Chionê
    Chionê is a figure from Greek mythology, often associated with snow and winter and appearing in various mythic traditions under slightly different name forms.
  • B. Gelo
    Gelo is a film featuring Spanish actress Ivana Baquero in a prominent role.
  • C. Givlaari
    Givlaari is an RNA interference-based therapy used to treat acute hepatic porphyria by reducing the production of toxic heme intermediates in the liver.
  • D. Gorely
    Gorely is an active stratovolcano complex on Russia’s Kamchatka Peninsula, known for its multiple craters, frequent eruptions, and striking acidic crater lakes.
  • E. Frosta
    Frosta is a rural municipality and peninsula in Trøndelag county, Norway, known for its fertile farmland and historical significance as a medieval assembly site.
  • 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_69d6aa61c15c8190a1839550c56e75e1 completed April 8, 2026, 7:20 p.m.
NER Named-entity recognition batch_69d73370e7388190885b104fc883456e completed April 9, 2026, 5:04 a.m.
NED1 Entity disambiguation (via context triple) batch_69de567a7ea0819088a2fa10f8367d89 completed April 14, 2026, 3 p.m.
NEDg Description generation batch_69de5eaf3cc08190935cb6ddf2020166 completed April 14, 2026, 3:35 p.m.
NED2 Entity disambiguation (via description) batch_69de63a902f4819089845bc6d7469c6b completed April 14, 2026, 3:56 p.m.
Created at: April 8, 2026, 9:18 p.m.