Triple
T4028518
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Woman's Hour |
E83649
|
entity |
| Predicate | hasRecurringTopic |
P24066
|
FINISHED |
| Object | gender equality |
—
|
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: gender equality | Statement: [Woman's Hour, hasRecurringTopic, gender equality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRecurringTopic Context triple: [Woman's Hour, hasRecurringTopic, gender equality]
-
A.
hasRecurringElement
Indicates that an entity includes an element that appears repeatedly or occurs multiple times within it.
-
B.
includesTopics
chosen
Indicates that one entity contains, covers, or addresses the specified topics as part of its content or scope.
-
C.
tienePeriodicidad
Indicates that something occurs, recurs, or is scheduled with a specific regular frequency or periodic pattern.
-
D.
hasMainPeriod
Indicates that something is associated with or characterized by a primary or most significant time period.
-
E.
recurringEvent
Indicates that an event occurs repeatedly over time according to some regular pattern or schedule.
- 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.