Triple

T15606835
Position Surface form Disambiguated ID Type / Status
Subject Serra da Lousã E375179 entity
Predicate contains P35 FINISHED
Object Talasnal
Talasnal is a restored schist mountain village in central Portugal known for its traditional stone houses, scenic forest setting, and rural tourism.
E1166850 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: Talasnal | Statement: [Serra da Lousã, contains, Talasnal]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Talasnal
Context triple: [Serra da Lousã, contains, Talasnal]
  • A. Talas
    Talas is a district and rapidly growing residential area of the central Anatolian city of Kayseri in Turkey.
  • B. Talne
    Talne is a small city in central Ukraine known for its historical architecture and location within Cherkasy Oblast.
  • C. Talador
    Talador is a war-torn, draenei-themed forest region on the world of Draenor in World of Warcraft, centered around the besieged city of Shattrath.
  • D. Torla
    Torla is a picturesque mountain village in the Spanish Pyrenees, serving as a main gateway to the Ordesa y Monte Perdido National Park.
  • E. Tialo
    Tialo is an Austronesian language of the Tomini–Tolitoli subgroup spoken in Central Sulawesi, Indonesia.
  • 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: Talasnal
Triple: [Serra da Lousã, contains, Talasnal]
Generated description
Talasnal is a restored schist mountain village in central Portugal known for its traditional stone houses, scenic forest setting, and rural tourism.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07
Target entity: Talasnal
Target entity description: Talasnal is a restored schist mountain village in central Portugal known for its traditional stone houses, scenic forest setting, and rural tourism.
  • A. Talas
    Talas is a district and rapidly growing residential area of the central Anatolian city of Kayseri in Turkey.
  • B. Talne
    Talne is a small city in central Ukraine known for its historical architecture and location within Cherkasy Oblast.
  • C. Talador
    Talador is a war-torn, draenei-themed forest region on the world of Draenor in World of Warcraft, centered around the besieged city of Shattrath.
  • D. Torla
    Torla is a picturesque mountain village in the Spanish Pyrenees, serving as a main gateway to the Ordesa y Monte Perdido National Park.
  • E. Tialo
    Tialo is an Austronesian language of the Tomini–Tolitoli subgroup spoken in Central Sulawesi, Indonesia.
  • 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_69d85ccf2794819096cda4cbcb02d478 completed April 10, 2026, 2:13 a.m.
NER Named-entity recognition batch_69e04e7ec08c8190b3842cf3043aea27 completed April 16, 2026, 2:50 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff56d51c28819097b8c2c0e2307401 completed May 9, 2026, 3:46 p.m.
NEDg Description generation batch_69ff57c304188190afa695ae88cf0234 completed May 9, 2026, 3:50 p.m.
NED2 Entity disambiguation (via description) batch_69ff5920436c81909addad5bb4566ae9 completed May 9, 2026, 3:56 p.m.
Created at: April 10, 2026, 4:13 a.m.