Triple
T33303842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Iverstown |
E852659
|
entity |
| Predicate | economicBasisInFiction |
P2313
|
FINISHED |
| Object | industry |
—
|
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: industry | Statement: [Iverstown, economicBasisInFiction, industry]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicBasisInFiction Context triple: [Iverstown, economicBasisInFiction, industry]
-
A.
hasFictionalEconomyBasedOn
Indicates that one fictional economy is modeled after, inspired by, or structurally derived from another specified economy.
-
B.
economicExtensionOf
Indicates that one entity’s economy is heavily dependent on, controlled by, or functions as an outgrowth of another entity’s economic system.
-
C.
basedOnInFiction
Indicates that a fictional work, character, or element is derived from, inspired by, or modeled after another real or fictional source.
-
D.
economicAspect
chosen
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
E.
economicSystem
Indicates the type or structure of the economic organization or system under which an entity operates or to which it belongs.
- 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_69f34966ed4c81908dc9dda82d8c7fe3 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69f73ae120bc8190bff94d38d7a7a00d |
completed | May 3, 2026, 12:09 p.m. |
| PD | Predicate disambiguation | batch_69f73a38d0848190aa5139144b8561c6 |
completed | May 3, 2026, 12:06 p.m. |
Created at: May 1, 2026, 1:33 a.m.