Triple
T14160932
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | U.S. Army Garrison Stuttgart |
E350941
|
entity |
| Predicate | hasChapelServices |
P77850
|
FINISHED |
| Object | religious support activities |
—
|
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: religious support activities | Statement: [U.S. Army Garrison Stuttgart, hasChapelServices, religious support activities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChapelServices Context triple: [U.S. Army Garrison Stuttgart, hasChapelServices, religious support activities]
-
A.
hasChapelUse
Indicates that something is used, designated, or functions as a chapel or for chapel-related purposes.
-
B.
hasChapelProgram
Indicates that an institution or organization offers or conducts a chapel program as part of its activities or services.
-
C.
hasChapelNearby
Indicates that one entity is located close to or in the vicinity of a chapel.
-
D.
hasChapelHonoring
Indicates that one entity contains or includes a chapel dedicated to honoring another entity.
-
E.
hasWorshipServices
chosen
Indicates that an entity conducts or provides organized religious worship services.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de61393f308190bb357e2bd1916f94 |
completed | April 14, 2026, 3:46 p.m. |
| PD | Predicate disambiguation | batch_69de05b8434c81908c33b1b513463b12 |
completed | April 14, 2026, 9:15 a.m. |
Created at: April 10, 2026, 12:59 a.m.