Triple
T7149923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia Convention |
E166665
|
entity |
| Predicate | adjacentEvent |
P45864
|
FINISHED |
| Object | ratification debates in the states |
—
|
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: ratification debates in the states | Statement: [Philadelphia Convention, adjacentEvent, ratification debates in the states]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentEvent Context triple: [Philadelphia Convention, adjacentEvent, ratification debates in the states]
-
A.
laterRelatedEvent
Indicates that one event is temporally related to another by occurring at a later time.
-
B.
isAdjacentTo
Indicates that one entity is directly next to or bordering another without anything of the same type in between.
-
C.
alternativeEvent
Indicates that one event serves as an alternative or substitute option to another event within the same context.
-
D.
hasNearbyEvent
chosen
Indicates that an event occurs close in space or time to the referenced entity.
-
E.
adjacentLandmark
Indicates that one landmark is located directly next to or very near another landmark, with no significant separation between them.
- 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_69c68886779c8190a8e3fbabffe68253 |
completed | March 27, 2026, 1:39 p.m. |
| NER | Named-entity recognition | batch_69c6e7f130e08190bc5ca99f90f9de92 |
completed | March 27, 2026, 8:26 p.m. |
| PD | Predicate disambiguation | batch_69c6e1caf4e48190b47bb398a3c1554d |
completed | March 27, 2026, 8 p.m. |
Created at: March 27, 2026, 2:46 p.m.