Triple
T21847671
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charpennes – Charles Hernu |
E539416
|
entity |
| Predicate | hasCode |
P9567
|
FINISHED |
| Object | Charpennes |
—
|
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: Charpennes | Statement: [Charpennes – Charles Hernu, hasCode, Charpennes]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Charpennes Context triple: [Charpennes – Charles Hernu, hasCode, Charpennes]
-
A.
Charpennes
chosen
Charpennes is a prominent urban district in the Lyon metropolitan area, known for its major transport hub and dense residential and commercial activity.
-
B.
Crouy
Crouy is a commune in northern France located in the Aisne department within the Hauts-de-France region.
-
C.
Gonesse
Gonesse is a commune in the northeastern suburbs of Paris, France, known historically as a rural town and now as part of the greater Paris metropolitan area.
-
D.
Essonnes
Essonnes was a former commune in northern France that later became part of the town of Corbeil-Essonnes in the Île-de-France region.
-
E.
Hurepoix
Hurepoix is a historic region of northern France, southwest of Paris, known for its rural landscapes and small towns such as Dourdan.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e0c476c3c88190a92d08ebb59a128a |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f0bd558ed88190a10b8d6752105cd6 |
completed | April 28, 2026, 1:59 p.m. |
Created at: April 16, 2026, 6:55 p.m.