Triple
T27558576
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fet |
E695709
|
entity |
| Predicate | hasCurrentSuccessorMunicipality |
P85884
|
FINISHED |
| Object | Lillestrøm |
—
|
NE NERFINISHED |
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: Lillestrøm | Statement: [Fet, hasCurrentSuccessorMunicipality, Lillestrøm]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCurrentSuccessorMunicipality Context triple: [Fet, hasCurrentSuccessorMunicipality, Lillestrøm]
-
A.
hasCitySuccessor
Indicates that one city is the successor or replacement of another city, typically in terms of status, function, or administrative role.
-
B.
successorInCity
Indicates that one entity directly follows or replaces another in holding a particular role, position, or function within the same city.
-
C.
hasCityServedSuccessor
Indicates that one city served by a service, role, or entity is the successor to another previously served city in that same context.
-
D.
hasSubdivisionSuccessor
chosen
Indicates that one administrative or territorial subdivision directly succeeds another in an ordered sequence or historical progression.
-
E.
successorParish
Indicates that one parish has formally succeeded another parish, taking over its ecclesiastical role or jurisdiction.
- 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_69ef5387e97c8190a9dab040d21cd048 |
completed | April 27, 2026, 12:16 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
Created at: April 27, 2026, 1:38 p.m.