Triple
T13105103
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | San Angeles |
E310823
|
entity |
| Predicate | hasEconomicAspectInFiction |
P55103
|
FINISHED |
| Object | corporate influence |
—
|
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: corporate influence | Statement: [San Angeles, hasEconomicAspectInFiction, corporate influence]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEconomicAspectInFiction Context triple: [San Angeles, hasEconomicAspectInFiction, corporate influence]
-
A.
hasFictionalEconomyBasedOn
Indicates that one fictional economy is modeled after, inspired by, or structurally derived from another specified economy.
-
B.
economicAspect
Indicates that something is related to, characterized by, or has implications for economic factors, conditions, or outcomes.
-
C.
hasEconomicDimension
Indicates that something involves, affects, or is characterized by economic factors, considerations, or consequences.
-
D.
hasEconomicContext
chosen
Indicates that something is associated with, influenced by, or situated within a particular economic situation, condition, or set of financial circumstances.
-
E.
hasFictionalEconomicActivity
Indicates that an entity is involved in an economic activity 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_69d806a872d08190a329806f8ff30df4 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98154c9f48190aeca779d97151759 |
completed | April 10, 2026, 11:01 p.m. |
| PD | Predicate disambiguation | batch_69d98041a3548190a05ddd83dbb660fa |
completed | April 10, 2026, 10:57 p.m. |
Created at: April 9, 2026, 9:05 p.m.