Triple
T562542
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Countess of Northesk |
E13483
|
entity |
| Predicate | traditionalUsage |
P6999
|
FINISHED |
| Object | held by the wife of the Earl of Northesk |
—
|
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: held by the wife of the Earl of Northesk | Statement: [Countess of Northesk, traditionalUsage, held by the wife of the Earl of Northesk]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: traditionalUsage Context triple: [Countess of Northesk, traditionalUsage, held by the wife of the Earl of Northesk]
-
A.
typicalPractice
Indicates that an action, behavior, or method is commonly or customarily done in a given context or by a given group.
-
B.
traditionalOrder
Indicates that entities are arranged or occur according to a customary, historically established sequence or hierarchy.
-
C.
modernUse
Indicates how something is currently used or applied in modern times.
-
D.
traditionalUse
chosen
Indicates that something is used or practiced according to long-established customs, habits, or cultural traditions.
-
E.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
- 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_69a4933edcf08190b35ecfd6014caee6 |
completed | March 1, 2026, 7:27 p.m. |
| NER | Named-entity recognition | batch_69a49a700e608190b235246df057bd9b |
completed | March 1, 2026, 7:58 p.m. |
| PD | Predicate disambiguation | batch_69a494c044648190a98589ab18935216 |
completed | March 1, 2026, 7:34 p.m. |
Created at: March 1, 2026, 7:32 p.m.