Triple
T438710
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Story Chapel |
E10066
|
entity |
| Predicate | hasSurroundings |
P13155
|
FINISHED |
| Object | cemetery landscape |
—
|
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: cemetery landscape | Statement: [Story Chapel, hasSurroundings, cemetery landscape]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSurroundings Context triple: [Story Chapel, hasSurroundings, cemetery landscape]
-
A.
surrounds
Indicates that one entity is located all around another entity, enclosing or encircling it on multiple sides or completely.
-
B.
hasNearbySquare
Indicates that one entity has at least one square-shaped entity located close to it in space.
-
C.
surroundedCity
Indicates that one city is encircled or completely enclosed by another city or its surrounding territory.
-
D.
hasEntrance
Indicates that one entity possesses or provides an entry point or access way to another entity or space.
-
E.
hasCorridor
Indicates that one entity includes, is connected by, or provides access through a corridor to another entity.
- F. None of above. chosen
Provenance (4 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_69a2e8465ef481909655c681b01e2986 |
completed | Feb. 28, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69a2ef283be881909444aaf257451747 |
completed | Feb. 28, 2026, 1:35 p.m. |
| PD | Predicate disambiguation | batch_69a2eddcf50c8190bfa0d1f8ee9f604a |
completed | Feb. 28, 2026, 1:30 p.m. |
| PDg | Predicate description generation | batch_69a2eeb9e6b0819093863959a6e5730a |
completed | Feb. 28, 2026, 1:33 p.m. |
Created at: Feb. 28, 2026, 1:11 p.m.