Triple
T33653923
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Relation between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957 |
E862170
|
entity |
| Predicate | dataStartYear |
P44250
|
FINISHED |
| Object | 1861 |
—
|
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: 1861 | Statement: [The Relation between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957, dataStartYear, 1861]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dataStartYear Context triple: [The Relation between Unemployment and the Rate of Change of Money Wage Rates in the United Kingdom, 1861–1957, dataStartYear, 1861]
-
A.
recordStartYear
chosen
Indicates the calendar year in which a particular record, entry, or data instance first began or was created.
-
B.
beganInYear
Indicates that an event, process, or state started in a specific calendar year.
-
C.
productionStartYear
Indicates the year in which the production of an item, work, or entity first began.
-
D.
typicalStartYear
Indicates the year in which something (such as an event, activity, or process) usually or customarily begins.
-
E.
dataAvailableFrom
Indicates that a specified source or provider offers access to certain data starting from a particular point or under certain conditions.
- 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_69f349840ba881908e3bfce536aeb92b |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_69f6fb19063c81909466b329655c8583 |
completed | May 3, 2026, 7:36 a.m. |
| PD | Predicate disambiguation | batch_69f6f96badb08190994442c2aba840b1 |
completed | May 3, 2026, 7:29 a.m. |
Created at: May 1, 2026, 1:42 a.m.