Triple
T14484443
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Helmer children |
E359190
|
entity |
| Predicate | resideInFictionalCity |
P47688
|
FINISHED |
| Object | unnamed Norwegian town |
—
|
LITERAL FINISHED |
How this triple was built (2 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: unnamed Norwegian town | Statement: [Helmer children, resideInFictionalCity, unnamed Norwegian town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: resideInFictionalCity Context triple: [Helmer children, resideInFictionalCity, unnamed Norwegian town]
-
A.
residesInFictionalLocation
chosen
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
-
B.
basedInFictionalLocation
Indicates that an entity’s primary setting, origin, or operations occur in a fictional (non-real) location.
-
C.
cityOfFictionalResidence
Indicates that a fictional character or entity resides in, or is associated with living in, a particular city within a narrative or fictional context.
-
D.
partOfFictionalCity
Indicates that one entity is a component, area, or subdivision within a larger fictional city.
-
E.
livesNearFictionalPlace
Indicates that one entity resides in close proximity to a fictional or imaginary location.
- F. None of above.
Provenance (3 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_69d8279740308190af9df93a3af8592e |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de924d7f4c8190b1f62b5ffe1ff649 |
completed | April 14, 2026, 7:15 p.m. |
| PD | Predicate disambiguation | batch_69de5c487b4c819097803e58dca628a5 |
completed | April 14, 2026, 3:24 p.m. |
Created at: April 10, 2026, 1:20 a.m.