Triple
T8492065
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Mayors |
E200994
|
entity |
| Predicate | hasFictionalGovernmentType |
P82060
|
FINISHED |
| Object | mayoral government on Terminus |
—
|
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: mayoral government on Terminus | Statement: [The Mayors, hasFictionalGovernmentType, mayoral government on Terminus]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFictionalGovernmentType Context triple: [The Mayors, hasFictionalGovernmentType, mayoral government on Terminus]
-
A.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
B.
hasFictionalLeader
Indicates that an entity is led or governed by a leader who is a fictional character rather than a real person.
-
C.
governedByFictional
Indicates that one entity is under the rule, control, or authority of another entity that is fictional or exists only in an imagined context.
-
D.
polityInFictionalWorld
chosen
Indicates that a political entity exists within, or is part of, a fictional world or universe.
-
E.
hasGovernmentTypeCountry
Indicates that a country possesses or is characterized by a particular form or type of government.
- 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_69ca831ee390819095fae73400bbfafc |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe55cf5dc81908cad31ac53e15b46 |
completed | March 31, 2026, 3:16 p.m. |
| PD | Predicate disambiguation | batch_69cbd107633c8190a36ba50e07876918 |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:13 p.m.