Triple
T5156911
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ruby, Oklahoma |
E116332
|
entity |
| Predicate | hasNearbyLocation |
P39585
|
FINISHED |
| Object | the Convent |
—
|
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: the Convent | Statement: [Ruby, Oklahoma, hasNearbyLocation, the Convent]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasNearbyLocation Context triple: [Ruby, Oklahoma, hasNearbyLocation, the Convent]
-
A.
nearbyLocation
Indicates that one location is situated close to another location in physical space.
-
B.
nearbyTo
Indicates that one entity is located close in distance or position to another entity.
-
C.
hasFormerUseNearby
Indicates that something in the vicinity previously had a particular use or function that is no longer current.
-
D.
hasNotableNearbyEntity
chosen
Indicates that one entity has another significant or noteworthy entity located in its close physical or contextual proximity.
-
E.
hasNearbyMode
Indicates that one entity has another entity located close enough to be considered in its immediate vicinity or surrounding area.
- 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_69bd445d94788190b72e2cc563120995 |
completed | March 20, 2026, 12:58 p.m. |
| NER | Named-entity recognition | batch_69bd79c1354c81908176703b4853c1a4 |
completed | March 20, 2026, 4:45 p.m. |
| PD | Predicate disambiguation | batch_69bd77b0fbb88190851e2d7ae1bdcc09 |
completed | March 20, 2026, 4:37 p.m. |
Created at: March 20, 2026, 1:44 p.m.