Triple
T15663960
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eidfjord |
E376637
|
entity |
| Predicate | hasPart |
P35
|
FINISHED |
| Object |
Hjølmo
Hjølmo is a small rural area in the municipality of Eidfjord in Vestland county, Norway, known for its scenic fjord and mountain surroundings.
|
E1171284
|
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: Hjølmo | Statement: [Eidfjord, hasPart, Hjølmo]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hjølmo Context triple: [Eidfjord, hasPart, Hjølmo]
-
A.
Hjelset
Hjelset is a village in Møre og Romsdal county, Norway, situated within Molde Municipality along the Romsdalsfjorden.
-
B.
Helge
Helge is a given name, used in various European countries, that is closely related to the name Helga.
-
C.
Hegge
Hegge is a small village in the municipality of Øystre Slidre in Innlandet county, Norway, known for its traditional rural setting and historic stave church.
-
D.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
E.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
- 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: Hjølmo Triple: [Eidfjord, hasPart, Hjølmo]
Generated description
Hjølmo is a small rural area in the municipality of Eidfjord in Vestland county, Norway, known for its scenic fjord and mountain surroundings.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Hjølmo Target entity description: Hjølmo is a small rural area in the municipality of Eidfjord in Vestland county, Norway, known for its scenic fjord and mountain surroundings.
-
A.
Hjelset
Hjelset is a village in Møre og Romsdal county, Norway, situated within Molde Municipality along the Romsdalsfjorden.
-
B.
Helge
Helge is a given name, used in various European countries, that is closely related to the name Helga.
-
C.
Hegge
Hegge is a small village in the municipality of Øystre Slidre in Innlandet county, Norway, known for its traditional rural setting and historic stave church.
-
D.
Helleren
Helleren is a small historic settlement in Norway known for its traditional houses built under a large rock overhang near the Jøssingfjord.
-
E.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
- 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_69d85cd1564c8190991adda63bfab4b0 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f0f4df08190ad2c5d78e435d8eb |
completed | April 16, 2026, 2:53 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ff6ed6f50c81909d87ced263064f0d |
completed | May 9, 2026, 5:28 p.m. |
| NEDg | Description generation | batch_69ff6fd9c968819098b2552a9deb0445 |
completed | May 9, 2026, 5:33 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ff708d42448190a53b90e00721eaa5 |
completed | May 9, 2026, 5:36 p.m. |
Created at: April 10, 2026, 4:16 a.m.