Triple
T28223282
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Attack on William H. Seward |
E711517
|
entity |
| Predicate | attackerDisguise |
P22080
|
FINISHED |
| Object | claimed to be delivering medicine |
—
|
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: claimed to be delivering medicine | Statement: [Attack on William H. Seward, attackerDisguise, claimed to be delivering medicine]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attackerDisguise Context triple: [Attack on William H. Seward, attackerDisguise, claimed to be delivering medicine]
-
A.
disguisedAs
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
B.
usesMasksOrDisguises
chosen
Indicates that an entity employs masks, costumes, or other forms of disguise to conceal or alter its identity in the context of an action or interaction.
-
C.
headquartersDisguise
Indicates that an entity’s headquarters is concealed, misrepresented, or disguised as something else.
-
D.
reasonForDisguise
Indicates the motive or purpose behind an entity adopting a disguise.
-
E.
attacker
Indicates a relationship where one entity initiates a harmful or hostile action against another entity.
- 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_69efb51dfb048190ada79b745c33b363 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f643530d38819090a74ea250785b82 |
completed | May 2, 2026, 6:32 p.m. |
| PD | Predicate disambiguation | batch_69f641e0fde08190bf06a1c5b388aa84 |
completed | May 2, 2026, 6:26 p.m. |
Created at: April 27, 2026, 10:48 p.m.