Triple
T17746450
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Charlie Cox |
E443001
|
entity |
| Predicate | eyeConditionPortrayedForRole |
P25307
|
FINISHED |
| Object | blindness (as Matt Murdock) |
—
|
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: blindness (as Matt Murdock) | Statement: [Charlie Cox, eyeConditionPortrayedForRole, blindness (as Matt Murdock)]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: eyeConditionPortrayedForRole Context triple: [Charlie Cox, eyeConditionPortrayedForRole, blindness (as Matt Murdock)]
-
A.
eyeCondition
chosen
Indicates that an entity has, experiences, or is characterized by a particular condition or disorder affecting the eyes.
-
B.
eyeCharacteristic
Indicates a relationship where an entity possesses a specific attribute, feature, or quality of its eyes.
-
C.
eyeAssociation
Indicates a relationship where one entity is associated with, linked to, or characterized by a particular eye or eye-related feature of another entity.
-
D.
eyeType
Indicates the specific kind or category of eyes an entity has, such as their form, structure, or visual style.
-
E.
eyeConditionCause
Indicates that one factor or event is the cause or contributing cause of a particular eye-related condition or disorder.
- 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_69d8b9ed3a2081909b2ec0d4dd2f4c37 |
completed | April 10, 2026, 8:50 a.m. |
| NER | Named-entity recognition | batch_69e47ad26940819090696c2cb86fd606 |
completed | April 19, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69e3cde9dc288190af0e2198487f2051 |
completed | April 18, 2026, 6:31 p.m. |
Created at: April 10, 2026, 10:09 a.m.