Triple
T11697096
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Andilly |
E278023
|
entity |
| Predicate | hasNeighbouringCommune |
P33892
|
FINISHED |
| Object | Margency |
E829727
|
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: Margency | Statement: [Andilly, hasNeighbouringCommune, Margency]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Margency Context triple: [Andilly, hasNeighbouringCommune, Margency]
-
A.
Margency
chosen
Margency is a small suburban commune in the Val-d'Oise department in northern France, located in the Île-de-France region near Paris.
-
B.
Marcelle
Marcelle is a given name, typically a feminine form of Marcel, used in various cultures.
-
C.
Blanchette
Blanchette is a French feminine given name and diminutive form of Blanche, traditionally meaning "white" or "fair."
-
D.
Pierrette
Pierrette is a French feminine given name, traditionally considered the female form of Pierre.
-
E.
Margot
Margot is the introspective, conflicted protagonist of the Canadian romantic drama film "Take This Waltz," whose emotional journey explores the complexities of love, desire, and long-term relationships.
- 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_69d6aafe02d881909900d54ad7d4af84 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a47cef60819088b7cc3a3a711e4c |
completed | April 10, 2026, 7:19 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ef1471cba88190a7abdcbf4f579ea9 |
completed | April 27, 2026, 7:46 a.m. |
Created at: April 8, 2026, 9:40 p.m.