Triple
T22204692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Porte de Montreuil |
E548773
|
entity |
| Predicate | hasMunicipalArrondissementNumber |
P47247
|
FINISHED |
| Object | 20 |
—
|
LITERAL 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: 20 | Statement: [Porte de Montreuil, hasMunicipalArrondissementNumber, 20]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMunicipalArrondissementNumber Context triple: [Porte de Montreuil, hasMunicipalArrondissementNumber, 20]
-
A.
hasArrondissement
Indicates a relationship where an administrative unit or locality is associated with, or belongs to, a specific arrondissement.
-
B.
hasNumberOfArrondissements
Indicates the relationship that specifies how many arrondissements (administrative districts) are associated with a given entity.
-
C.
hasMunicipalDistrictNumber
chosen
Indicates that a municipality or local administrative unit is assigned a specific district number within its municipal structure.
-
D.
capitalOfArrondissement
Indicates that a place serves as the administrative capital (seat) of a specified arrondissement.
-
E.
hasMunicipalPart
Indicates that an administrative or territorial entity includes a municipality as one of its constituent parts.
- 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_69e11e3ecc7c8190b5f94cd8f42e9d37 |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f12b27451081908c29d1915b6c4229 |
completed | April 28, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69e71b4dcc408190a30429fb08fcf39e |
completed | April 21, 2026, 6:38 a.m. |
Created at: April 16, 2026, 8:36 p.m.