Triple
T34778193
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sergeant Tom Croydon |
E1002560
|
entity |
| Predicate | locatedInTheFictionalUniverse |
P98600
|
FINISHED |
| Object | rural Victoria |
—
|
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: rural Victoria | Statement: [Sergeant Tom Croydon, locatedInTheFictionalUniverse, rural Victoria]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locatedInTheFictionalUniverse Context triple: [Sergeant Tom Croydon, locatedInTheFictionalUniverse, rural Victoria]
-
A.
locatedInFictionalContext
chosen
Indicates that one entity exists or occurs within the setting or universe of a fictional work associated with another entity.
-
B.
basedInFictionalSetting
Indicates that an entity’s primary location or setting exists within a fictional or imaginary world rather than the real world.
-
C.
isSetInFictionalUniverse
Indicates that a narrative work takes place within a specific fictional universe or setting.
-
D.
residesInFictionalLocation
Indicates that an entity lives or is based in a location that is explicitly fictional or imaginary.
-
E.
locatedInFictionalEvent
Indicates that one entity (typically a place, object, or character) exists or occurs within the context or setting of a fictional event.
- 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_69f76db30a108190bb57ca95b873e5bb |
completed | May 3, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_6a037c8c34f88190ace26f555827f23e |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379fd7aac8190873077e63873aa72 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 3:59 p.m.