Triple
T13704873
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Thomas Kent |
E328613
|
entity |
| Predicate | usesDisguiseOf |
P20150
|
FINISHED |
| Object | young male actor |
—
|
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: young male actor | Statement: [Thomas Kent, usesDisguiseOf, young male actor]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesDisguiseOf Context triple: [Thomas Kent, usesDisguiseOf, young male actor]
-
A.
usesMasksOrDisguises
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.
-
B.
disguisedAs
chosen
Indicates that one entity is intentionally presenting itself as, or made to appear as, another entity in order to conceal its true identity.
-
C.
reasonForDisguise
Indicates the motive or purpose behind an entity adopting a disguise.
-
D.
headquartersDisguise
Indicates that an entity’s headquarters is concealed, misrepresented, or disguised as something else.
-
E.
isCostumed
Indicates that an entity is wearing or otherwise adorned with a costume.
- 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_69d8076ff62081908a7bd79889edd7a0 |
completed | April 9, 2026, 8:09 p.m. |
| NER | Named-entity recognition | batch_69dcad17732c8190bbd0d73107711c99 |
completed | April 13, 2026, 8:45 a.m. |
| PD | Predicate disambiguation | batch_69dbbe9059488190a8113177c83e1481 |
completed | April 12, 2026, 3:47 p.m. |
Created at: April 9, 2026, 9:54 p.m.