Triple
T14372514
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Daniel Wellington |
E356389
|
entity |
| Predicate | offersWomenWatches |
P113773
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Daniel Wellington, offersWomenWatches, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersWomenWatches Context triple: [Daniel Wellington, offersWomenWatches, true]
-
A.
watches
Indicates that one entity observes or views another entity or event, typically by looking at it attentively over a period of time.
-
B.
watchesVia
Indicates that one entity views or consumes content through a particular medium, platform, or device.
-
C.
womenSection
Indicates that something is designated as belonging to, located in, or associated with the women's section or area.
-
D.
viewOnWomen
Indicates a person's attitudes, beliefs, or perspectives regarding women and gender roles.
-
E.
watchMovementType
Indicates the type of mechanical or electronic movement mechanism that drives how a watch operates.
- 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_69d8279163a081908aec45c0e3f1e02f |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de8fb2082c8190b42cc5f2bab4f574 |
completed | April 14, 2026, 7:04 p.m. |
| PD | Predicate disambiguation | batch_69de2a9cb3e081909f6b33fdd939bb9e |
completed | April 14, 2026, 11:53 a.m. |
| PDg | Predicate description generation | batch_69de2e07d1f88190bdcd20967e484718 |
completed | April 14, 2026, 12:07 p.m. |
Created at: April 10, 2026, 1:15 a.m.