Triple
T30284711
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Montmorency forest |
E770201
|
entity |
| Predicate | isUrbanPeripheryForest |
P90278
|
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: [Montmorency forest, isUrbanPeripheryForest, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isUrbanPeripheryForest Context triple: [Montmorency forest, isUrbanPeripheryForest, true]
-
A.
isUrbanForest
Indicates that an area of trees and vegetation is located within or closely integrated with an urban or suburban environment.
-
B.
isUrbanFringeSite
chosen
Indicates that a site is located on the transitional boundary between urban development and surrounding rural or undeveloped areas.
-
C.
isUrbanizedAround
Indicates that an area or region has developed urban characteristics or infrastructure surrounding a particular location or feature.
-
D.
isUrbanized
Indicates that a place or area has been developed with dense human settlement, infrastructure, and built environment characteristic of a city or town.
-
E.
isUrbanDistrict
Indicates that a given district is classified as an urban administrative or residential area rather than a rural one.
- 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_69f224868fa8819099127eaf8855a28f |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69f6810772408190b1d8db5d0b9bfbaa |
completed | May 2, 2026, 10:56 p.m. |
| PD | Predicate disambiguation | batch_69f678ce54b081908c26edfd49e39c60 |
completed | May 2, 2026, 10:21 p.m. |
Created at: April 29, 2026, 7:45 p.m.