Triple
T31824359
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Amaya |
E812349
|
entity |
| Predicate | wearsInCivilianForm |
P172639
|
FINISHED |
| Object | glasses |
—
|
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: glasses | Statement: [Amaya, wearsInCivilianForm, glasses]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: wearsInCivilianForm Context triple: [Amaya, wearsInCivilianForm, glasses]
-
A.
usedPlainClothes
Indicates that an entity carried out an action or role while wearing ordinary, non-uniform clothing to avoid being recognized in an official capacity.
-
B.
uniformedOrPlainclothes
Indicates that an entity is characterized as either wearing a uniform or dressed in plain clothes in the context of the described situation.
-
C.
wearsOnUniform
Indicates that an item is part of and is worn as a component of a uniform.
-
D.
hasCivilianIdentity
Indicates that an entity possesses a non-superhero, everyday personal identity used in civilian life.
-
E.
woreUniformOf
Indicates that one entity was dressed in or used the official uniform associated with another entity (such as an organization, group, or role).
- 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_69f348e97fa48190aa06286962af6dee |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6b034bc74819091250f91ba5174c0 |
completed | May 3, 2026, 2:17 a.m. |
| PD | Predicate disambiguation | batch_69f6aca59d4881908d14ed47962703bd |
completed | May 3, 2026, 2:02 a.m. |
| PDg | Predicate description generation | batch_69f6af7d92008190aead47eaae8cc091 |
completed | May 3, 2026, 2:14 a.m. |
Created at: April 30, 2026, 11:46 p.m.