Triple
T13971467
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Chilly-Mazarin |
E336073
|
entity |
| Predicate | locatedNear |
P294
|
FINISHED |
| Object | Morangis |
E333072
|
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: Morangis | Statement: [Chilly-Mazarin, locatedNear, Morangis]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morangis Context triple: [Chilly-Mazarin, locatedNear, Morangis]
-
A.
Morangis
chosen
Morangis is a commune in the southern suburbs of Paris, located in the Essonne department in the Île-de-France region of northern France.
-
B.
Martelange
Martelange is a small Belgian town known for straddling the border with Luxembourg and serving as a local commercial and transit hub.
-
C.
Beaufays
Beaufays is a village in the municipality of Chaudfontaine in the province of Liège, Belgium.
-
D.
Fernelmont
Fernelmont is a rural municipality in the province of Namur in Wallonia, Belgium, known for its agricultural landscape and small villages.
-
E.
Rodange
Rodange is a town in southwestern Luxembourg known as an important railway junction near the Belgian and French borders.
- 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_69d81c61f3508190aaf2ca0dc0002c59 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de2e8eae40819080dd4bd25c73b6d6 |
completed | April 14, 2026, 12:09 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fba1df334c8190a3d65198cc3d11f6 |
completed | May 6, 2026, 8:17 p.m. |
Created at: April 9, 2026, 10:18 p.m.