Triple
T28262184
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | deserts the army for Carmen |
E712610
|
entity |
| Predicate | hasCharacterPatient |
P180501
|
FINISHED |
| Object | Carmen |
—
|
NE NERFINISHED |
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: Carmen | Statement: [deserts the army for Carmen, hasCharacterPatient, Carmen]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCharacterPatient Context triple: [deserts the army for Carmen, hasCharacterPatient, Carmen]
-
A.
hasPatient
Indicates that an action, event, or process involves a specific entity as the one undergoing or receiving its effects (the patient).
-
B.
hasPatientRole
Indicates that an entity participates in a relationship or activity specifically in the role of a patient (the one receiving care, treatment, or action).
-
C.
hasHealthCareCharacteristic
Indicates that an entity possesses a specific healthcare-related attribute, quality, or feature.
-
D.
hasHumanCharacters
Indicates that the subject includes or features characters that are human beings.
-
E.
hasCharacters
Indicates that an entity (such as a work or story) includes or features certain characters as part of its content.
- 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_69efb5207eb08190827e4c34048030b1 |
completed | April 27, 2026, 7:12 p.m. |
| NER | Named-entity recognition | batch_69f7431c0eec81909ead443e07d75e18 |
completed | May 3, 2026, 12:44 p.m. |
| PD | Predicate disambiguation | batch_69f74143cf708190a12d487884298437 |
completed | May 3, 2026, 12:36 p.m. |
| PDg | Predicate description generation | batch_69f7431aac148190bb6aac59817c174a |
completed | May 3, 2026, 12:44 p.m. |
Created at: April 27, 2026, 11:12 p.m.