Triple
T9686731
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L’Enfant Promenade |
E234427
|
entity |
| Predicate | hasLandscapeElements |
P22129
|
FINISHED |
| Object | paved walkways |
—
|
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: paved walkways | Statement: [L’Enfant Promenade, hasLandscapeElements, paved walkways]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLandscapeElements Context triple: [L’Enfant Promenade, hasLandscapeElements, paved walkways]
-
A.
hasLandscapeType
Indicates that an entity possesses or is characterized by a particular type or category of landscape.
-
B.
hasLandscapeFeatures
chosen
Indicates that an entity possesses or includes specific landscape-related characteristics or elements.
-
C.
hasLandComponent
Indicates that something includes, consists of, or is associated with a land-based part or portion as one of its components.
-
D.
hasDiverseLandscape
Indicates that an entity possesses a variety of distinct physical or environmental features within its geographic area.
-
E.
hasPortrait
Indicates that one entity possesses, displays, or is associated with a portrait depicting another entity.
- 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_69ca84ca73208190957a900c8543bdcc |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9cd2dab481908e0d3fed28de9d40 |
completed | April 1, 2026, 10:31 p.m. |
| PD | Predicate disambiguation | batch_69ccd5b840f081909f66bf0b66d17d9b |
completed | April 1, 2026, 8:22 a.m. |
Created at: March 30, 2026, 8:17 p.m.