Triple
T11686406
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Émile Haug |
E277755
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object |
Haug
Haug is a surname of Germanic origin borne by various notable individuals across different fields.
|
E940977
|
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: Haug | Statement: [Émile Haug, familyName, Haug]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Haug Context triple: [Émile Haug, familyName, Haug]
-
A.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
B.
Hestnes
Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
-
C.
Valle-Hovin
Valle-Hovin is a residential and recreational neighborhood in Oslo, Norway, known for its sports facilities and event venues.
-
D.
Harestua
Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
-
E.
Hjorthagen
Hjorthagen is a residential district in northeastern Stockholm, Sweden, known for its mix of historic workers’ housing and modern developments near the Royal National City Park and the Värtan harbor 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: Haug Triple: [Émile Haug, familyName, Haug]
Generated description
Haug is a surname of Germanic origin borne by various notable individuals across different fields.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Haug Target entity description: Haug is a surname of Germanic origin borne by various notable individuals across different fields.
-
A.
Hafslund
Hafslund is a major Norwegian energy and utility company known for its role in electricity production, distribution, and related services.
-
B.
Hestnes
Hestnes is a small settlement located within the municipality of Eigersund in Rogaland county, southwestern Norway.
-
C.
Valle-Hovin
Valle-Hovin is a residential and recreational neighborhood in Oslo, Norway, known for its sports facilities and event venues.
-
D.
Harestua
Harestua is a village in Viken county, Norway, known for its residential community and proximity to the Harestua Solar Observatory.
-
E.
Hjorthagen
Hjorthagen is a residential district in northeastern Stockholm, Sweden, known for its mix of historic workers’ housing and modern developments near the Royal National City Park and the Värtan harbor 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a4654be881909bd0256cf18e25de |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1433be908190b2ac887655a6c85a |
completed | April 27, 2026, 7:45 a.m. |
| NEDg | Description generation | batch_69ef511f8f688190b2806d4e8ab16511 |
completed | April 27, 2026, 12:05 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69ef537efcc48190afffaa50f28940d8 |
completed | April 27, 2026, 12:15 p.m. |
Created at: April 8, 2026, 9:40 p.m.