Triple
T24914218
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lakon people |
E623931
|
entity |
| Predicate | hasCustomaryInstitution |
P35306
|
FINISHED |
| Object | chiefly system |
—
|
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: chiefly system | Statement: [Lakon people, hasCustomaryInstitution, chiefly system]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomaryInstitution Context triple: [Lakon people, hasCustomaryInstitution, chiefly system]
-
A.
hasFinancialInstitution
Indicates that one entity is associated with or linked to a financial institution, such as a bank or similar financial service provider.
-
B.
hasStateInstitution
Indicates that a particular state possesses, governs, or is served by a specific institution operating under its authority or within its jurisdiction.
-
C.
hasInstitutions
Indicates that one entity possesses, contains, or is associated with one or more institutions.
-
D.
hasLocalInstitution
Indicates that a given place or region possesses or hosts an institution that operates locally within its boundaries.
-
E.
hasTraditionalInstitutions
chosen
Indicates that an entity possesses or is associated with long-established, customary social, cultural, or governance institutions.
- 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_69e2fac889c081908e9ff686cb428e5a |
completed | April 18, 2026, 3:30 a.m. |
| NER | Named-entity recognition | batch_69f657f653448190a945b4751af8507d |
completed | May 2, 2026, 8 p.m. |
| PD | Predicate disambiguation | batch_69f6575ba12081909396036f78757a76 |
completed | May 2, 2026, 7:58 p.m. |
Created at: April 18, 2026, 5:28 a.m.