Triple

T20137634
Position Surface form Disambiguated ID Type / Status
Subject Harju maakond E491063 entity
Predicate contains P35 FINISHED
Object Kehra
Kehra is a small town in northern Estonia known for its paper industry and location along the Jägala River.
 E1413438 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: Kehra | Statement: [Harju maakond, contains, Kehra]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Kehra
Context triple: [Harju maakond, contains, Kehra]
  • A. Kehre
    Kehre is a key concept in Martin Heidegger’s philosophy denoting a decisive “turn” or shift in his thinking about Being and the history of Western metaphysics.
  • B. Kaei
    Kaei was a Japanese era name (nengō) of the late Edo period, notable for encompassing events such as the arrival of Commodore Perry and the opening of Japan to the West.
  • C. Kaei
    Kaei is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
  • D. Kezlev
    Kezlev is the historical Crimean Tatar name for the city now known as Eupatoria, a coastal town on the western shore of Crimea.
  • E. Keratea
    Keratea is a town in eastern Attica, Greece, known for its historical significance and proximity to the Athens metropolitan area.
  • 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: Kehra
Triple: [Harju maakond, contains, Kehra]
Generated description
Kehra is a small town in northern Estonia known for its paper industry and location along the Jägala River.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Kehra
Target entity description: Kehra is a small town in northern Estonia known for its paper industry and location along the Jägala River.
  • A. Kehre
    Kehre is a key concept in Martin Heidegger’s philosophy denoting a decisive “turn” or shift in his thinking about Being and the history of Western metaphysics.
  • B. Kaei
    Kaei was a Japanese era name (nengō) of the late Edo period, notable for encompassing events such as the arrival of Commodore Perry and the opening of Japan to the West.
  • C. Kaei
    Kaei is an alternate name for the Kayeli language, an Austronesian language historically spoken on Buru Island in Indonesia.
  • D. Kezlev
    Kezlev is the historical Crimean Tatar name for the city now known as Eupatoria, a coastal town on the western shore of Crimea.
  • E. Keratea
    Keratea is a town in eastern Attica, Greece, known for its historical significance and proximity to the Athens metropolitan area.
  • 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_69da62651a0c8190a3e05e95e056a66b completed April 11, 2026, 3:01 p.m.
NER Named-entity recognition batch_69e6676879f48190a59da04393d2a8cc completed April 20, 2026, 5:50 p.m.
NED1 Entity disambiguation (via context triple) batch_6a082de4bba88190a7d20a03826cbff0 completed May 16, 2026, 8:42 a.m.
NEDg Description generation batch_6a082ee3aafc819088a14b0a5d655072 completed May 16, 2026, 8:46 a.m.
NED2 Entity disambiguation (via description) batch_6a082f70e24881909c43a85289df4976 completed May 16, 2026, 8:48 a.m.
Created at: April 11, 2026, 11:32 p.m.