Triple
T36385081
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juan Mardo |
E896169
|
entity |
| Predicate | characterComplexity |
P200889
|
FINISHED |
| Object | complex role |
—
|
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: complex role | Statement: [Juan Mardo, characterComplexity, complex role]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterComplexity Context triple: [Juan Mardo, characterComplexity, complex role]
-
A.
characterContrast
Indicates a relationship where two characters are compared to highlight their opposing or significantly differing traits, roles, or behaviors.
-
B.
textualCharacterization
Indicates that one entity provides a descriptive or narrative characterization of another entity, typically in textual form.
-
C.
characterResolution
Indicates the process or outcome by which a character’s conflicts, arcs, or internal struggles are brought to a conclusion or clarified within a narrative.
-
D.
agingCharacteristics
Indicates how the qualities, properties, or behavior of something change as it ages or over time.
-
E.
characterReveals
Indicates that one character discloses or makes known information, feelings, or intentions to another character.
- 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_69f76e51d358819092bbc5f119f49476 |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69ffb69812808190a751853b30183e65 |
completed | May 9, 2026, 10:35 p.m. |
| PD | Predicate disambiguation | batch_69ffb63bdda88190a9dd8426dc0bad43 |
completed | May 9, 2026, 10:33 p.m. |
| PDg | Predicate description generation | batch_69ffb6976f84819098a9b14946591baa |
completed | May 9, 2026, 10:35 p.m. |
Created at: May 3, 2026, 4:10 p.m.