Triple
T33777156
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Francilienne (A104/N104) |
E865552
|
entity |
| Predicate | relationToParis |
P136519
|
FINISHED |
| Object | beyond A86 ring road |
—
|
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: beyond A86 ring road | Statement: [Francilienne (A104/N104), relationToParis, beyond A86 ring road]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: relationToParis Context triple: [Francilienne (A104/N104), relationToParis, beyond A86 ring road]
-
A.
relationshipToParis
chosen
Indicates the specific type of connection or association an entity has with Paris.
-
B.
relationshipToRelative
Indicates the specific familial connection or kinship role that one person has in relation to a particular relative.
-
C.
relationToAndrewMartin
Indicates a relationship that specifies how one entity is connected or related to Andrew Martin.
-
D.
relationshipToMoscow
Indicates the type or nature of a connection, association, or relevance that something has specifically to Moscow.
-
E.
relationToVonMaur
Indicates a specified type of relationship or association that an entity has with Von Maur.
- 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_69f3498df6f88190bf9647ea4e4a956e |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037e0953908190b2930b3c06a40129 |
completed | May 12, 2026, 7:22 p.m. |
| PD | Predicate disambiguation | batch_6a0379f6c3308190b954f7810214ceed |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:45 a.m.