Triple
T14748778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Artis Martineau |
E346545
|
entity |
| Predicate | healthStatusAtProgramEntry |
P115633
|
FINISHED |
| Object | terminally ill |
—
|
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: terminally ill | Statement: [Artis Martineau, healthStatusAtProgramEntry, terminally ill]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: healthStatusAtProgramEntry Context triple: [Artis Martineau, healthStatusAtProgramEntry, terminally ill]
-
A.
healthStatusBeforeDeath
Indicates the condition or state of an entity’s health immediately prior to its death.
-
B.
healthIndicator
Indicates a measure or signal that reflects the health status or condition of an entity.
-
C.
currentPhysicalStatus
Indicates the present condition or state of an entity’s physical being or body.
-
D.
hasHealthCode
Indicates that an entity is associated with a specific health-related classification or status code.
-
E.
hasHealthProgram
Indicates that an entity provides, administers, or is associated with a specific health-related program or initiative.
- F. None of above. chosen
Provenance (4 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_69d822e6f1c88190bc494d491a907114 |
completed | April 9, 2026, 10:06 p.m. |
| NER | Named-entity recognition | batch_69dec7d2e1748190b16ede681fe52872 |
completed | April 14, 2026, 11:03 p.m. |
| PD | Predicate disambiguation | batch_69de8bf9331481909582045cd567d91f |
completed | April 14, 2026, 6:48 p.m. |
| PDg | Predicate description generation | batch_69de8f4b67cc8190b84b59fcec5cf579 |
completed | April 14, 2026, 7:02 p.m. |
Created at: April 10, 2026, 1:30 a.m.