Triple
T87779
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beaver |
E1764
|
entity |
| Predicate | cargoStatusDuringBostonTeaParty |
P4071
|
FINISHED |
| Object | destroyed |
—
|
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: destroyed | Statement: [Beaver, cargoStatusDuringBostonTeaParty, destroyed]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: cargoStatusDuringBostonTeaParty Context triple: [Beaver, cargoStatusDuringBostonTeaParty, destroyed]
-
A.
shipUsed
Indicates that a particular ship was employed or utilized in carrying out an event, activity, or operation.
-
B.
wasColonialPower
Indicates that one entity historically exercised colonial control or dominance over another entity.
-
C.
shipInvolved
Indicates that a ship participates in, is associated with, or plays a role in a specified event or situation.
-
D.
historicallyBorneBy
Indicates that an entity has carried, possessed, or used another entity (such as a name, title, or symbol) at some point in the past.
-
E.
hasHarbor
Indicates that a place possesses or contains a harbor for docking or sheltering vessels.
- 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.