Triple
T29778319
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Young Doctors |
E755441
|
entity |
| Predicate | locationOfFictionalHospital |
P107457
|
FINISHED |
| Object | Sydney |
—
|
NE NERFINISHED |
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: Sydney | Statement: [The Young Doctors, locationOfFictionalHospital, Sydney]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: locationOfFictionalHospital Context triple: [The Young Doctors, locationOfFictionalHospital, Sydney]
-
A.
fictionalHospital
Indicates that a hospital is imaginary or exists only within a fictional or narrative context, rather than in reality.
-
B.
hospitalLocation
chosen
Indicates the geographic place or address where a hospital is situated.
-
C.
fictionalHeadquartersLocation
Indicates the place where a fictional organization, group, or entity is based or has its main headquarters within a fictional context.
-
D.
locatedOnFictionalRoute
Indicates that something is situated along or associated with a route that exists only within a fictional or imaginary setting.
-
E.
locationOfFacility
Indicates that a facility is situated at or associated with a specific geographic location.
- 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_69f0ef878574819088c867fd1a5c8b86 |
completed | April 28, 2026, 5:33 p.m. |
| NER | Named-entity recognition | batch_6a0056174c908190be99c91a70393e47 |
completed | May 10, 2026, 9:55 a.m. |
| PD | Predicate disambiguation | batch_6a00538e7e08819091ecd4316cd641a1 |
completed | May 10, 2026, 9:44 a.m. |
Created at: April 28, 2026, 8:48 p.m.