Triple
T5665778
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Old Frisian |
E124852
|
entity |
| Predicate | numberOfCasesApprox |
P1437
|
FINISHED |
| Object | 4 |
—
|
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: 4 | Statement: [Old Frisian, numberOfCasesApprox, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfCasesApprox Context triple: [Old Frisian, numberOfCasesApprox, 4]
-
A.
numberOfCases
Indicates the total count of individual instances, occurrences, or records associated with a particular situation, condition, or category.
-
B.
hasNumberOfCasesApprox
chosen
Indicates that an entity is associated with an approximate (not exact) count of cases.
-
C.
numberOfProbableCases
Indicates the quantified count of cases that are considered likely or suspected to occur or have occurred, based on available evidence or criteria.
-
D.
typeOfCasesHandled
Indicates the categories or kinds of cases that an entity (such as a person, organization, or system) is responsible for managing or processing.
-
E.
defendantCount
Indicates the number of defendants involved in a particular legal case or proceeding.
- 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_69c00828906881908966f270b8f130cf |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c0236d3f94819095111c41a323612d |
completed | March 22, 2026, 5:14 p.m. |
| PD | Predicate disambiguation | batch_69c021ba4ec481909db8cdbf0e907dd6 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:43 p.m.