Triple
T87797
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaver |
E1764
|
entity |
| Predicate | partOfSeriesOfEvents |
P4074
|
FINISHED |
| Object | escalation leading to American Revolutionary War |
—
|
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: escalation leading to American Revolutionary War | Statement: [Beaver, partOfSeriesOfEvents, escalation leading to American Revolutionary War]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: partOfSeriesOfEvents Context triple: [Beaver, partOfSeriesOfEvents, escalation leading to American Revolutionary War]
-
A.
isSeriesOf
Indicates that one entity is a sequence or set of related items that collectively form a series associated with another entity.
-
B.
partOfCampaign
Indicates that an entity participates in, belongs to, or is included within a specific campaign.
-
C.
participatedInEvent
Indicates that an entity took part in or was actively involved in a specific event.
-
D.
significantEvent
Indicates that an event involving the entities is of notable importance or impact within a given context.
-
E.
event
Indicates that there exists an occurrence or happening involving one or more entities, typically situated in time and possibly space.
- 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_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. |
| PDg | Predicate description generation | batch_69a2503c12808190a3cbb7b171f466f0 |
completed | Feb. 28, 2026, 2:17 a.m. |
Created at: Feb. 28, 2026, 2:06 a.m.