Triple

T8327776
Position Surface form Disambiguated ID Type / Status
Subject Lofa County E194997 entity
Predicate hasCity P316 FINISHED
Object Foya
Foya is a town in northwestern Liberia that serves as an important local center for trade and administration in Lofa County.
 E725267 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: Foya | Statement: [Lofa County, hasCity, Foya]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Foya
Context triple: [Lofa County, hasCity, Foya]
  • A. Fakui
    Fakui is the given name of Zhang Fakui, a notable Chinese military figure.
  • B. Faraulep
    Faraulep is a small atoll and municipality in the Federated States of Micronesia, located in the western Pacific Ocean as part of Yap State.
  • C. Faeto
    Faeto is a small town in southern Italy known for its unique linguistic heritage, including the rare Franco-Provençal dialect Faetar.
  • D. Fata
    Fata are the Roman personifications of fate, equivalent to the Parcae, who determine the destinies and lifespans of humans and gods.
  • E. Lavia
    Lavia is a small municipality in southwestern Finland known for its rural landscapes and proximity to the town of Sastamala.
  • 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: Foya
Triple: [Lofa County, hasCity, Foya]
Generated description
Foya is a town in northwestern Liberia that serves as an important local center for trade and administration in Lofa County.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Foya
Target entity description: Foya is a town in northwestern Liberia that serves as an important local center for trade and administration in Lofa County.
  • A. Fakui
    Fakui is the given name of Zhang Fakui, a notable Chinese military figure.
  • B. Faraulep
    Faraulep is a small atoll and municipality in the Federated States of Micronesia, located in the western Pacific Ocean as part of Yap State.
  • C. Faeto
    Faeto is a small town in southern Italy known for its unique linguistic heritage, including the rare Franco-Provençal dialect Faetar.
  • D. Fata
    Fata are the Roman personifications of fate, equivalent to the Parcae, who determine the destinies and lifespans of humans and gods.
  • E. Lavia
    Lavia is a small municipality in southwestern Finland known for its rural landscapes and proximity to the town of Sastamala.
  • 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_69ca82e87f2c8190bdb71ee29dfc642d completed March 30, 2026, 2:04 p.m.
NER Named-entity recognition batch_69cb7f8243288190b1ae74d69395fc91 completed March 31, 2026, 8:02 a.m.
NED1 Entity disambiguation (via context triple) batch_69cd95b92708819097795498f9ebcdfc completed April 1, 2026, 10:01 p.m.
NEDg Description generation batch_69cdab60ec308190a9001f9235e556b4 completed April 1, 2026, 11:33 p.m.
NED2 Entity disambiguation (via description) batch_69cdb2e3457c8190a2d0cb6eeb81c9ef completed April 2, 2026, 12:05 a.m.
Created at: March 30, 2026, 5:56 p.m.