Triple
T31735174
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Complaints |
E809973
|
entity |
| Predicate | hasProtagonistDepartment |
P112090
|
FINISHED |
| Object | Complaints and Conduct Department |
—
|
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: Complaints and Conduct Department | Statement: [The Complaints, hasProtagonistDepartment, Complaints and Conduct Department]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasProtagonistDepartment Context triple: [The Complaints, hasProtagonistDepartment, Complaints and Conduct Department]
-
A.
hasProtagonist
Indicates that a work of narrative has a main character who serves as its central focus or driving agent.
-
B.
hasProtagonistFromSource
Indicates that a work’s main character originates from, or is derived from, a specified source (such as another work, franchise, or medium).
-
C.
hasDepartmentInStory
chosen
Indicates that a particular story includes or is associated with a specific department.
-
D.
hasSpiritProtagonist
Indicates that the primary or central character in a narrative is a spirit or non-corporeal being.
-
E.
hasProtagonistGroup
Indicates that a narrative work features a central group of characters who collectively serve as the main protagonists.
- 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_69f348e0e4908190a884582eca646fb7 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_6a008098e5dc8190b7ccad8bab780343 |
completed | May 10, 2026, 12:56 p.m. |
| PD | Predicate disambiguation | batch_6a008037267c8190990225a6ff0b3694 |
completed | May 10, 2026, 12:55 p.m. |
Created at: April 30, 2026, 11:23 p.m.