Triple
T5507531
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Delaford |
E144476
|
entity |
| Predicate | hasEstateIncomeInFiction |
P14482
|
FINISHED |
| Object | Colonel Brandon’s landed income |
—
|
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: Colonel Brandon’s landed income | Statement: [Delaford, hasEstateIncomeInFiction, Colonel Brandon’s landed income]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEstateIncomeInFiction Context triple: [Delaford, hasEstateIncomeInFiction, Colonel Brandon’s landed income]
-
A.
hasFictionalEconomicActivity
Indicates that an entity is involved in an economic activity that exists only in a fictional or imaginary context.
-
B.
hasFictionComponent
Indicates that something includes, contains, or is composed in part of a fictional element or work.
-
C.
hasFictionalProprietor
chosen
Indicates that something is owned, managed, or run by a fictional character or entity within a narrative context.
-
D.
hasFictionalWork
Indicates that one entity is the creator, owner, or source of a fictional work associated with another entity.
-
E.
hasFictionalProperty
Indicates that an entity possesses a property, attribute, or characteristic that exists only in a fictional or imaginary context.
- 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_69c008f6b5048190a09064116062cf69 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c01f495c588190b0cfe5bfb3d2c221 |
completed | March 22, 2026, 4:56 p.m. |
| PD | Predicate disambiguation | batch_69c01b07bde08190b3933b96bdc70dd5 |
completed | March 22, 2026, 4:38 p.m. |
Created at: March 22, 2026, 3:32 p.m.