Triple
T4566695
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Baron |
E121925
|
entity |
| Predicate | oftenLinkedTo |
P37
|
FINISHED |
| Object | barony as territorial unit |
—
|
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: barony as territorial unit | Statement: [Baron, oftenLinkedTo, barony as territorial unit]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenLinkedTo Context triple: [Baron, oftenLinkedTo, barony as territorial unit]
-
A.
oftenAccompaniedBy
Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another entity.
-
B.
oftenInvolvedWith
Indicates that one entity frequently participates in or is commonly associated with activities, events, or situations involving another entity.
-
C.
associatedWithSee
Indicates a relationship where one entity is contextually or functionally linked to another through the act or concept of seeing or visual observation.
-
D.
relatedTo
chosen
Indicates a general, non-specific relationship or association exists between two entities.
-
E.
relatedType
Indicates that one entity is connected to another through a specified type or category of relationship.
- 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_69bd463f156881908a99aca69c5721ac |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd589e35808190aa609bb04b128dbe |
completed | March 20, 2026, 2:24 p.m. |
| PD | Predicate disambiguation | batch_69bd5227063c8190973155a875b013a7 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:09 p.m.