Triple
T15098694
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Michael Kors watches |
E360605
|
entity |
| Predicate | oftenPurchasedFor |
P43920
|
FINISHED |
| Object | gifts |
—
|
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: gifts | Statement: [Michael Kors watches, oftenPurchasedFor, gifts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: oftenPurchasedFor Context triple: [Michael Kors watches, oftenPurchasedFor, gifts]
-
A.
isOftenPurchasedAs
chosen
Indicates that one item is frequently bought together with, or in conjunction with, another item.
-
B.
oftenSoughtOn
Indicates that one entity is frequently searched for, requested, or pursued in relation to another entity.
-
C.
oftenUsedAfter
Indicates that one entity is frequently or typically used immediately following another entity in a sequence or workflow.
-
D.
oftenUse
Indicates that one entity frequently or regularly uses, employs, or utilizes another entity.
-
E.
oftenAccompaniedBy
Indicates that one entity is frequently found together with, occurs alongside, or is commonly associated in presence or use with another 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_69d85a035aa88190b52a139d3a1b7b6d |
completed | April 10, 2026, 2:01 a.m. |
| NER | Named-entity recognition | batch_69e0054f00388190a5123d9f4a869b96 |
completed | April 15, 2026, 9:38 p.m. |
| PD | Predicate disambiguation | batch_69deb9645b9c8190a5712456dbd78029 |
completed | April 14, 2026, 10:02 p.m. |
Created at: April 10, 2026, 3:04 a.m.