Triple
T2005556
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Roberta, Georgia |
E43572
|
entity |
| Predicate | isLocalCrossroads |
P35084
|
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: [Roberta, Georgia, isLocalCrossroads, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: isLocalCrossroads Context triple: [Roberta, Georgia, isLocalCrossroads, true]
-
A.
hasMajorCrossing
Indicates that one entity has a significant or primary intersection or crossing with another entity.
-
B.
locationDuring_Operation Crossroads
Indicates that an entity was located at a particular place during the time period of Operation Crossroads.
-
C.
crossesNear
Indicates that one entity passes across the path or area of another entity at a location that is close to, but not directly intersecting, the other entity.
-
D.
hasTrafficIsland
Indicates the presence of a traffic island separating or organizing lanes or directions of vehicular movement within a roadway.
-
E.
isMajorInterchangeFor
Indicates that one location functions as a primary hub where multiple routes or lines connect or transfer between each other for another location.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb898795481909920c1a4c4d62c2d |
completed | March 7, 2026, 5:33 a.m. |
| PD | Predicate disambiguation | batch_69abb79e63c08190982c8b44a557266f |
completed | March 7, 2026, 5:29 a.m. |
| PDg | Predicate description generation | batch_69abb87b9fc08190a748c278ef2d7dc7 |
completed | March 7, 2026, 5:32 a.m. |
Created at: March 4, 2026, 7:37 p.m.