Triple
T28904861
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London, Airstrip One |
E733043
|
entity |
| Predicate | economicConditionInFiction |
P13811
|
FINISHED |
| Object | chronic shortages |
—
|
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: chronic shortages | Statement: [London, Airstrip One, economicConditionInFiction, chronic shortages]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: economicConditionInFiction Context triple: [London, Airstrip One, economicConditionInFiction, chronic shortages]
-
A.
hasFictionalEconomyBasedOn
Indicates that one fictional economy is modeled after, inspired by, or structurally derived from another specified economy.
-
B.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
-
C.
worksUnderInFiction
Indicates that, within a fictional context or narrative, one character or entity is hierarchically subordinate to and takes direction from another.
-
D.
conductsInFiction
Indicates that an entity carries out or performs an action or role within a fictional context or narrative.
-
E.
stateInFiction
chosen
Indicates that a particular state or condition exists within a fictional context or narrative world rather than in real-world actuality.
- 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_69f05b096d208190958a57d2e4b5a93a |
completed | April 28, 2026, 7 a.m. |
| NER | Named-entity recognition | batch_69f69edbb7648190bd89c57e0932eac1 |
completed | May 3, 2026, 1:03 a.m. |
| PD | Predicate disambiguation | batch_69f69d17e8d48190b30bcc2f4bd81eb2 |
completed | May 3, 2026, 12:55 a.m. |
Created at: April 28, 2026, 8:06 a.m.