Triple
T25489864
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Uthiyan Cheralathan |
E638808
|
entity |
| Predicate | literaryCharacterization |
P32702
|
FINISHED |
| Object | valorous warrior |
—
|
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: valorous warrior | Statement: [Uthiyan Cheralathan, literaryCharacterization, valorous warrior]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: literaryCharacterization Context triple: [Uthiyan Cheralathan, literaryCharacterization, valorous warrior]
-
A.
textualCharacterization
Indicates that one entity provides a descriptive or narrative characterization of another entity, typically in textual form.
-
B.
literaryFeature
Indicates a relationship where something possesses or exhibits a characteristic, device, or stylistic element used in literature.
-
C.
characterSetting
Indicates that a character is associated with, appears in, or is situated within a particular setting or environment.
-
D.
characterDescription
chosen
Indicates that one entity provides a textual description or portrayal of the characteristics, traits, or attributes of another entity.
-
E.
literaryRole
Indicates the specific narrative or functional role an entity holds within a literary work or text.
- 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_69e75dbabeac8190bab30628f8b799d4 |
completed | April 21, 2026, 11:21 a.m. |
| NER | Named-entity recognition | batch_69f621fcea1481909b6f8b3af1ee6820 |
completed | May 2, 2026, 4:10 p.m. |
| PD | Predicate disambiguation | batch_69f620dc38088190b56b2b15ed75b3c2 |
completed | May 2, 2026, 4:05 p.m. |
Created at: April 21, 2026, 2:34 p.m.