Triple
T2188774
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | James A. Michener |
E49812
|
entity |
| Predicate | spouse |
P13
|
FINISHED |
| Object |
Vange Nord
Vange Nord was the wife of American author James A. Michener.
|
E242315
|
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: Vange Nord | Statement: [James A. Michener, spouse, Vange Nord]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Vange Nord Context triple: [James A. Michener, spouse, Vange Nord]
-
A.
Vårby
Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
-
B.
Vadsø
Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
-
C.
Maarkedal
Maarkedal is a rural municipality in the Flemish Ardennes of East Flanders, Belgium, known for its hilly landscape and cycling routes.
-
D.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
E.
Viggbyholm
Viggbyholm is a residential urban area in the northern Stockholm region of Sweden, known for its proximity to water, green spaces, and commuter connections into central Stockholm.
- 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: Vange Nord Triple: [James A. Michener, spouse, Vange Nord]
Generated description
Vange Nord was the wife of American author James A. Michener.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Vange Nord Target entity description: Vange Nord was the wife of American author James A. Michener.
-
A.
Vårby
Vårby is a suburban district in the southern Stockholm area of Sweden, known for its residential neighborhoods and proximity to Lake Mälaren.
-
B.
Vadsø
Vadsø is a small coastal town and administrative center in Finnmark, known for its Arctic location on the Varanger Peninsula and its role as a hub of Sami and Kven culture in Northern Norway.
-
C.
Maarkedal
Maarkedal is a rural municipality in the Flemish Ardennes of East Flanders, Belgium, known for its hilly landscape and cycling routes.
-
D.
Svaneke
Svaneke is a picturesque coastal town on the Danish island of Bornholm, known for its well-preserved half-timbered houses, harbor, and traditional smokehouses.
-
E.
Viggbyholm
Viggbyholm is a residential urban area in the northern Stockholm region of Sweden, known for its proximity to water, green spaces, and commuter connections into central Stockholm.
- 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_69a88aaba3c48190b351cab9b26989ff |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abbf373c608190b7716c137b3e9fe9 |
completed | March 7, 2026, 6:01 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ae5dada268819082ddc4acd58e19f3 |
completed | March 9, 2026, 5:42 a.m. |
| NEDg | Description generation | batch_69ae5e5fe37c8190bcf73200d32f5faa |
completed | March 9, 2026, 5:45 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ae5ed1e3208190b46d5e8361c2a5f6 |
completed | March 9, 2026, 5:46 a.m. |
Created at: March 4, 2026, 7:46 p.m.