Triple
T1094228
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bustan |
E24234
|
entity |
| Predicate | mainConcern |
P6371
|
FINISHED |
| Object | practical ethics |
—
|
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: practical ethics | Statement: [Bustan, mainConcern, practical ethics]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: mainConcern Context triple: [Bustan, mainConcern, practical ethics]
-
A.
concern
Indicates that one entity is about, relates to, or is of interest or importance to another entity.
-
B.
concernsRight
Indicates that something is about or relates specifically to a legal or moral right held by an entity.
-
C.
majorIssue
chosen
Indicates that something is a primary or most significant problem, concern, or obstacle in a given context.
-
D.
raisedConcernAbout
Indicates that one entity has expressed worry, doubt, or objection regarding another entity or issue.
-
E.
narrativeConcern
Indicates a relationship where something is thematically or structurally focused on, revolves around, or is primarily about a particular narrative topic or issue.
- 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_69a4940542308190ac2a0b1f730b7cfc |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b99d1e8c81909cf1178d68d38885 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b743175481908f3967e589717c55 |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.