Triple
T35131509
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | the Arconia |
E1014447
|
entity |
| Predicate | hasTenantsInFiction |
P97696
|
FINISHED |
| Object | residents of diverse backgrounds |
—
|
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: residents of diverse backgrounds | Statement: [the Arconia, hasTenantsInFiction, residents of diverse backgrounds]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTenantsInFiction Context triple: [the Arconia, hasTenantsInFiction, residents of diverse backgrounds]
-
A.
hasFictionalInhabitants
chosen
Indicates that a place or setting is inhabited by fictional or imaginary beings.
-
B.
hasCustomerBaseInFiction
Indicates that an entity’s primary or significant group of customers exists within fictional works or fictional contexts.
-
C.
hasFictionalEstablishmentType
Indicates that an establishment is associated with a particular type or category of fictional setting or institution.
-
D.
livesInFiction
Indicates that one entity exists or resides within the fictional world or narrative setting created by another entity.
-
E.
hasBranchInFictionalLocation
Indicates that an organization maintains a branch, office, or presence within a fictional or imaginary location.
- 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_69f76dd9c1848190af70d4882a2c1ad7 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69fe59d11e9881909d2f33b7c717030e |
completed | May 8, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69fe394fdfbc8190a931926ae3635cbf |
completed | May 8, 2026, 7:28 p.m. |
Created at: May 3, 2026, 4:02 p.m.