Triple
T14601486
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stange |
E342714
|
entity |
| Predicate | hasVillage |
P4011
|
FINISHED |
| Object | Ottestad |
E1061830
|
NE 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: Ottestad | Statement: [Stange, hasVillage, Ottestad]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ottestad Context triple: [Stange, hasVillage, Ottestad]
-
A.
Ottestad
chosen
Ottestad is a village in Innlandet county, Norway, situated within Stange municipality just south of the city of Hamar.
-
B.
Ossuccio
Ossuccio is a small lakeside locality on the western shore of Lake Como in northern Italy, known for its scenic setting opposite the historic Isola Comacina.
-
C.
Stößen
Stößen is a small town in the German state of Saxony-Anhalt that forms part of the broader Leipzig metropolitan area.
-
D.
Etsaut
Etsaut is a small mountain commune in southwestern France, located in the Pyrenees near the Spanish border.
-
E.
Toinette
Toinette is the sharp-witted, outspoken maid in Molière’s comedy "Le Malade imaginaire," known for her clever schemes and satirical commentary on her hypochondriac master.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d822dec68081908c2553145c4051dc |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69deb438748081908020ce04b869866a |
completed | April 14, 2026, 9:40 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fd94cc9fbc819090ae4efe9bc618aa |
completed | May 8, 2026, 7:46 a.m. |
Created at: April 10, 2026, 1:25 a.m.