Triple
T3349998
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Avenue Jean Médecin |
E70465
|
entity |
| Predicate | hasSideStreets |
P36837
|
FINISHED |
| Object | Rue du Maréchal Joffre vicinity |
—
|
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: Rue du Maréchal Joffre vicinity | Statement: [Avenue Jean Médecin, hasSideStreets, Rue du Maréchal Joffre vicinity]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSideStreets Context triple: [Avenue Jean Médecin, hasSideStreets, Rue du Maréchal Joffre vicinity]
-
A.
hasSecondaryStreet
Indicates that an entity is associated with an additional, non-primary street address or roadway.
-
B.
hasConnectingStreet
chosen
Indicates that two locations are linked by a street that directly connects them.
-
C.
hasStreet
Indicates that an entity is located on, associated with, or identified by a particular street.
-
D.
hasNearbyStreet
Indicates that one entity is located close to or adjacent to a street.
-
E.
hasNotableStreet
Indicates that an entity is associated with a particular street that is considered notable or significant.
- 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_69ad85a4ef7c8190a29e2bbd6fa454e4 |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adb21f3ae48190a33530712da01bc3 |
completed | March 8, 2026, 5:30 p.m. |
| PD | Predicate disambiguation | batch_69ada42df1d48190874bb05f95deefde |
completed | March 8, 2026, 4:30 p.m. |
Created at: March 8, 2026, 3:12 p.m.