Triple
T87784
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaver |
E1764
|
entity |
| Predicate | involvedInConflict |
P1406
|
FINISHED |
| Object | American colonial resistance to Tea Act |
—
|
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: American colonial resistance to Tea Act | Statement: [Beaver, involvedInConflict, American colonial resistance to Tea Act]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: involvedInConflict Context triple: [Beaver, involvedInConflict, American colonial resistance to Tea Act]
-
A.
conflictIn
chosen
Indicates that one entity is involved in, associated with, or occurs within a particular conflict or dispute.
-
B.
militaryConflict
Indicates a relationship where two or more parties are engaged in organized, armed hostilities or warfare against each other.
-
C.
involvedCountry
Indicates that a country participates in, is associated with, or is otherwise implicated in the referenced event, activity, or situation.
-
D.
associatedWithWar
Indicates a relationship where an entity is connected or related to war, such as by involvement, influence, cause, or context.
-
E.
conflictSide
Indicates that an entity participates as a distinct party or faction on one side of a conflict or dispute.
- 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_69a24c8150408190910a693eb51c1f71 |
completed | Feb. 28, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69a2503d304c8190a0034ffa4a38a501 |
completed | Feb. 28, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69a24eb6da2c8190a33d144d219f7abe |
completed | Feb. 28, 2026, 2:11 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.