Triple
T32530515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kayenta Health Center |
E831438
|
entity |
| Predicate | hasEmergencyCapability |
P142603
|
FINISHED |
| Object | limited emergency stabilization |
—
|
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: limited emergency stabilization | Statement: [Kayenta Health Center, hasEmergencyCapability, limited emergency stabilization]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasEmergencyCapability Context triple: [Kayenta Health Center, hasEmergencyCapability, limited emergency stabilization]
-
A.
hasEmergencyFeature
chosen
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.
hasEmergencyServices
Indicates that the subject provides or is equipped with emergency response services (such as police, fire, or medical assistance).
-
D.
hasEmergencyLevel
Indicates that an entity is associated with a specific degree or severity of emergency status.
-
E.
hasEmergencySystems
Indicates that the subject is equipped with or includes systems designed to detect, respond to, or manage emergency situations.
- 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_69f34924b1cc8190ad3aca0c0f012a7e |
completed | April 30, 2026, 12:20 p.m. |
| NER | Named-entity recognition | batch_69f6c8159edc8190b1c87015e0c820e8 |
completed | May 3, 2026, 3:59 a.m. |
| PD | Predicate disambiguation | batch_69f6c3f42fbc8190a06eb1044c9e6094 |
completed | May 3, 2026, 3:41 a.m. |
Created at: May 1, 2026, 1:01 a.m.