Triple
T11036880
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Stephen McGann |
E260907
|
entity |
| Predicate | fieldOfWriting |
P97423
|
FINISHED |
| Object | medical history |
—
|
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: medical history | Statement: [Stephen McGann, fieldOfWriting, medical history]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: fieldOfWriting Context triple: [Stephen McGann, fieldOfWriting, medical history]
-
A.
literarySubject
Indicates that one entity serves as the subject, topic, or focus of a literary work created by another entity.
-
B.
fieldOfExpertiseInFiction
Indicates that a fictional character or entity is portrayed as having specialized knowledge, skill, or professional focus in a particular field or domain.
-
C.
languageOfWritings
Indicates that a specified language is the one in which certain writings or written works are composed.
-
D.
currentlyWrittenIn
Indicates that a work or document is, at the present time, expressed or composed in a particular language or writing system.
-
E.
workInFiction
Indicates that one entity is a fictional work in which the other entity appears or is set.
- 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_69d6aa979bdc8190bf0e79104cc098c1 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d797e9e3fc8190802195ac9fcb8e28 |
completed | April 9, 2026, 12:13 p.m. |
| PD | Predicate disambiguation | batch_69d74407cb088190ba37c8da3d342b64 |
completed | April 9, 2026, 6:15 a.m. |
| PDg | Predicate description generation | batch_69d750c99f9881908ee2b01b6ce4b3a1 |
completed | April 9, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:25 p.m.