Triple
T34102526
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bègles |
E874608
|
entity |
| Predicate | isSuburbanCommune |
P94313
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bègles, isSuburbanCommune, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isSuburbanCommune Context triple: [Bègles, isSuburbanCommune, true]
-
A.
isSuburbanCommunity
Indicates that a community is located in a suburban area, typically characterized by residential neighborhoods situated between urban centers and rural regions.
-
B.
isSuburbanCommunityIn
Indicates that a suburban community is located within or belongs to a specified larger geographic or administrative area.
-
C.
isSuburbanMunicipality
chosen
Indicates that a municipality is located in a suburban area, typically surrounding or adjacent to a larger urban center.
-
D.
isSuburbanArea
Indicates that a location is characterized as a suburban area, typically lying between urban and rural regions and exhibiting suburban development patterns.
-
E.
isRuralSuburbanCommunity
Indicates that a community is characterized by a mix of rural and suburban features, typically lying between fully urbanized and sparsely populated rural areas.
- 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_69f349a80d4481908527317d43f5c579 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71c35327c8190884f1bfe12bd2cd7 |
completed | May 3, 2026, 9:58 a.m. |
| PD | Predicate disambiguation | batch_69f71822d0e88190ac9731c7ae5a4def |
completed | May 3, 2026, 9:40 a.m. |
Created at: May 1, 2026, 1:53 a.m.