Triple
T36155927
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sydney drinking water supply system |
E1045732
|
entity |
| Predicate | hasEmergencySource |
P184963
|
FINISHED |
| Object | Sydney Desalination Plant |
E2171365
|
NE 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: Sydney Desalination Plant | Statement: [Sydney drinking water supply system, hasEmergencySource, Sydney Desalination Plant]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencySource Context triple: [Sydney drinking water supply system, hasEmergencySource, Sydney Desalination Plant]
-
A.
hasEmergencyFeature
Indicates that an entity includes or supports a special function or capability intended for use in emergency situations.
-
B.
hasEmergencyServiceProvider
Indicates that an entity is associated with or served by a specific emergency service provider (such as police, fire, or medical services).
-
C.
hasEmergencyLevel
Indicates that an entity is associated with a specific degree or severity of emergency status.
-
D.
hasEmergencyAlarm
Indicates that an entity is equipped with or associated with an emergency alarm system that can be activated in urgent situations.
-
E.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
- F. None of above. chosen
Provenance (5 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_69f76e38903c8190a52887620f90aabe |
completed | May 3, 2026, 3:48 p.m. |
| NER | Named-entity recognition | batch_69f7b69b333081909cadbed3fcb8ecf5 |
completed | May 3, 2026, 8:56 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a393409873081908145bccf18448dd8 |
completed | June 22, 2026, 1:09 p.m. |
| PD | Predicate disambiguation | batch_69f7b4c2a5f8819094ad4621d7b97e0c |
completed | May 3, 2026, 8:49 p.m. |
| PDg | Predicate description generation | batch_69f7b69a74a08190b31b1201278a2c57 |
completed | May 3, 2026, 8:56 p.m. |
Created at: May 3, 2026, 4:08 p.m.