Triple
T24200075
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | General John Stark Day |
E599949
|
entity |
| Predicate | honoreeConflict |
P150618
|
FINISHED |
| Object | American Revolutionary War |
—
|
NE NERFINISHED |
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: American Revolutionary War | Statement: [General John Stark Day, honoreeConflict, American Revolutionary War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: honoreeConflict Context triple: [General John Stark Day, honoreeConflict, American Revolutionary War]
-
A.
honorsConflict
Indicates that one entity acknowledges and respects an existing conflict or competing obligation involving another entity or situation.
-
B.
mentionsConflict
Indicates that one entity refers to or discusses a dispute, disagreement, or conflict involving another entity.
-
C.
conflictsAwardedIn
chosen
Indicates that an award or recognition was given in the context of a specific conflict or set of conflicts.
-
D.
notableConflictWith
Indicates a significant, recognized conflict or dispute that exists or has existed between the related entities.
-
E.
facedConflictOver
Indicates that two or more entities experienced opposition, dispute, or tension concerning a particular issue, resource, or situation.
- 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_69e288ceaab88190899d0acb5931591d |
completed | April 17, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69f27ca08874819081dd6613ac462c40 |
completed | April 29, 2026, 9:48 p.m. |
| PD | Predicate disambiguation | batch_69f1c43e55688190b55fc20274ed471c |
completed | April 29, 2026, 8:41 a.m. |
Created at: April 17, 2026, 11:36 p.m.