Triple
T35020936
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | London cyber-conversion factory (Pete’s World) |
E1010192
|
entity |
| Predicate | conversionTargets |
P79397
|
FINISHED |
| Object | homeless people |
—
|
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: homeless people | Statement: [London cyber-conversion factory (Pete’s World), conversionTargets, homeless people]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: conversionTargets Context triple: [London cyber-conversion factory (Pete’s World), conversionTargets, homeless people]
-
A.
conversionTarget
chosen
Indicates that one entity serves as the intended outcome, goal, or result that another entity is meant to be converted or transformed into.
-
B.
conversionProcess
Indicates a process in which something is transformed or changed from one state, form, or representation into another.
-
C.
conversionMode
Indicates the specific method or setting by which one form, unit, or representation is transformed into another.
-
D.
conversionContext
Indicates the situational or environmental factors under which a conversion (e.g., change of state, format, or belief) occurs or is interpreted.
-
E.
convertsTo
Indicates that one entity is transformed or changed into another entity, typically resulting in a different state, form, or representation.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69f7b0e5744c8190a22c1e1d6fcfa466 |
completed | May 3, 2026, 8:32 p.m. |
| PD | Predicate disambiguation | batch_69f7ab70d034819080295628497d8582 |
completed | May 3, 2026, 8:09 p.m. |
Created at: May 3, 2026, 4:01 p.m.