Triple
T4028515
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman's Hour |
E83649
|
entity |
| Predicate | hasFormatChange |
P12309
|
FINISHED |
| Object | introduction of podcast version |
—
|
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: introduction of podcast version | Statement: [Woman's Hour, hasFormatChange, introduction of podcast version]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormatChange Context triple: [Woman's Hour, hasFormatChange, introduction of podcast version]
-
A.
mostRecentFormatChange
Indicates the most recent modification made to the format or structure of an entity, relative to all prior format changes.
-
B.
formatMayChange
Indicates that the format or structure of something is subject to modification and may not remain consistent over time.
-
C.
hasResultingChange
Indicates that one entity causes or leads to a specific change or transformation in another entity or state.
-
D.
hadMultipleFormatsOverTime
chosen
Indicates that the same underlying item or entity has existed in more than one format or version at different points in time.
-
E.
hasFileFormat
Indicates that one entity (typically a digital file or resource) is encoded, stored, or represented using a specific file format defined by the other entity.
- 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_69aed92e29ac819080f7a98b594fec05 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaf066b08190afbb4a18ddc8d67e |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fc78ec819092d4dab88d85a141 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:36 p.m.