Triple
T35208044
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Becky Lynch |
E1016592
|
entity |
| Predicate | hasMerchandiseBasedOn |
P45835
|
FINISHED |
| Object | The Man |
—
|
NE NERFINISHED |
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: The Man | Statement: [Becky Lynch, hasMerchandiseBasedOn, The Man]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMerchandiseBasedOn Context triple: [Becky Lynch, hasMerchandiseBasedOn, The Man]
-
A.
hasProduct
Indicates that an entity possesses, offers, or is associated with a particular product.
-
B.
hasExtensiveMerchandise
Indicates that an entity offers a large and varied range of merchandise or products.
-
C.
merchandiseSource
Indicates that one entity is the origin, supplier, or provider from which another entity’s merchandise is obtained.
-
D.
hasMerchandiseTieIn
chosen
Indicates that one entity has a commercial or promotional product or line (merchandise) that is directly tied to, branded with, or derived from another entity.
-
E.
usedInMerchandise
Indicates that something (such as a work, character, or design) is utilized or featured as part of a merchandise item.
- 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff289541e0819096eeceb8e6332650 |
completed | May 9, 2026, 12:29 p.m. |
| PD | Predicate disambiguation | batch_69ff281ab1988190920f0443be9f10cc |
completed | May 9, 2026, 12:27 p.m. |
Created at: May 3, 2026, 4:02 p.m.