Triple
T10846907
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 4*Town |
E256034
|
entity |
| Predicate | hasMerchandiseInUniverse |
P79243
|
FINISHED |
| Object | posters |
—
|
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: posters | Statement: [4*Town, hasMerchandiseInUniverse, posters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMerchandiseInUniverse Context triple: [4*Town, hasMerchandiseInUniverse, posters]
-
A.
hasMerchandiseTieIn
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.
-
B.
hasFictionalUniverseElement
Indicates that one entity is a component, feature, or constituent part of the fictional universe represented by the other entity.
-
C.
usedInMerchandise
chosen
Indicates that something (such as a work, character, or design) is utilized or featured as part of a merchandise item.
-
D.
inUniverseProductType
Indicates that a product belongs to or is categorized within a specific fictional or defined universe or setting.
-
E.
inUniverseMaterial
Indicates that something is made of or composed from a material that exists within a specified fictional or conceptual universe.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75113bc188190ac78df0c51d95de6 |
completed | April 9, 2026, 7:11 a.m. |
| PD | Predicate disambiguation | batch_69d70d2b51448190bae748ed6c23edde |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:20 p.m.