Triple
T11203918
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Factory Act 1833 |
E265108
|
entity |
| Predicate | numberOfInspectorsCreated |
P97840
|
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: [Factory Act 1833, numberOfInspectorsCreated, 4]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInspectorsCreated Context triple: [Factory Act 1833, numberOfInspectorsCreated, 4]
-
A.
numberOfCircuitJudgesCreated
Indicates the total count of circuit judge positions that have been established or created.
-
B.
numberOfInstances
Indicates the quantity or count of distinct occurrences or instances associated with a given entity or context.
-
C.
numberOfDetectors
Indicates the quantity of detectors associated with or involved in a given entity or system.
-
D.
numberOfAuditoria
Indicates the total count of auditoria associated with or contained within a given entity.
-
E.
numberOfInvestigations
Indicates the count of investigations associated with or conducted by a given entity.
- F. None of above. chosen
Provenance (4 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_69d6aa9eb9248190b20211772621b4bc |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7e8d355c481908fc3d555b596314d |
completed | April 9, 2026, 5:58 p.m. |
| PD | Predicate disambiguation | batch_69d75cf83464819087529d47d025d313 |
completed | April 9, 2026, 8:02 a.m. |
| PDg | Predicate description generation | batch_69d77062271c8190b63da714ab5beff9 |
completed | April 9, 2026, 9:24 a.m. |
Created at: April 8, 2026, 9:30 p.m.