Triple
T36805661
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Rummy Mitchens |
E909442
|
entity |
| Predicate | economicStatusInFiction |
P77957
|
FINISHED |
| Object | impoverished |
—
|
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: impoverished | Statement: [Rummy Mitchens, economicStatusInFiction, impoverished]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicStatusInFiction Context triple: [Rummy Mitchens, economicStatusInFiction, impoverished]
-
A.
economicStatus
Indicates the financial or socioeconomic condition or standing of an entity relative to others or to defined economic criteria.
-
B.
fictionalSocialClass
chosen
Indicates a relationship where an entity is assigned to or associated with a social class that exists only within a fictional or imagined context.
-
C.
fictionalStatus
Indicates that an entity exists only in imagination or narrative and does not correspond to a real-world counterpart.
-
D.
hasFictionalEconomyBasedOn
Indicates that one fictional economy is modeled after, inspired by, or structurally derived from another specified economy.
-
E.
wealthDescribedAs
Indicates that one entity’s wealth is characterized, portrayed, or expressed in terms of another entity or description.
- 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_69f76e7cbbf48190891227b14d041139 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69fb563aec448190875410fb1a3ed624 |
completed | May 6, 2026, 2:54 p.m. |
| PD | Predicate disambiguation | batch_69fb35b9ede881908aaae93a215525df |
completed | May 6, 2026, 12:36 p.m. |
Created at: May 3, 2026, 4:12 p.m.