Triple
T38108483
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Physician's Tale |
E951585
|
entity |
| Predicate | characterAppius |
P201663
|
FINISHED |
| Object | represents judicial tyranny |
—
|
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: represents judicial tyranny | Statement: [The Physician's Tale, characterAppius, represents judicial tyranny]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characterAppius Context triple: [The Physician's Tale, characterAppius, represents judicial tyranny]
-
A.
eraCharacter
Indicates that a character is associated with, or belongs to, a particular historical or fictional era.
-
B.
MarcusAquilaPortrayedBy
Indicates that one entity is the actor or performer who portrays the character Marcus Aquila.
-
C.
romanNomen
Indicates that an entity has a specific Roman nomen, i.e., the clan or gens name within the traditional Roman naming system.
-
D.
charioteerOf
Indicates that one entity serves as the driver or controller of a chariot belonging to or associated with another entity.
-
E.
ArgiveCommander
Indicates a relationship where an entity holds the role or status of a commander associated with Argos or the Argives.
- 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_69f76f065ed08190bdfb1b6d817f5b39 |
completed | May 3, 2026, 3:51 p.m. |
| NER | Named-entity recognition | batch_6a0010e46d948190a51111b5270fade7 |
completed | May 10, 2026, 5 a.m. |
| PD | Predicate disambiguation | batch_6a001061d34c8190bfe73f3d7c061eb7 |
completed | May 10, 2026, 4:58 a.m. |
| PDg | Predicate description generation | batch_6a0010e304a08190a4d0a4fa11a9a3b3 |
completed | May 10, 2026, 5 a.m. |
Created at: May 3, 2026, 4:21 p.m.