Triple
T9754139
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ramone |
E236511
|
entity |
| Predicate | shopSpecialty |
P90808
|
FINISHED |
| Object | custom paint |
—
|
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: custom paint | Statement: [Ramone, shopSpecialty, custom paint]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: shopSpecialty Context triple: [Ramone, shopSpecialty, custom paint]
-
A.
hasSpecials
Indicates that an entity offers or is associated with special deals, promotions, or limited-time offers.
-
B.
featuresShop
Indicates that an entity prominently presents or includes a particular shop as one of its notable elements or offerings.
-
C.
styleSpecialty
Indicates a relationship where an entity’s expertise, focus, or specialization is in a particular style or stylistic approach.
-
D.
uniformSpecialty
Indicates that multiple entities share the same specific specialty, expertise, or area of focus.
-
E.
marketSpecialization
Indicates a relationship where an entity focuses its activities, products, or services on serving a specific segment or niche of a broader market.
- 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_69ca84d4eddc8190996fec1417d2bae8 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9fb01ad08190b2435fa505c622bc |
completed | April 1, 2026, 10:44 p.m. |
| PD | Predicate disambiguation | batch_69cd03d0772c8190bd1750cf1cfba309 |
completed | April 1, 2026, 11:38 a.m. |
| PDg | Predicate description generation | batch_69cd081a9c5c819093439be7e802ff85 |
completed | April 1, 2026, 11:57 a.m. |
Created at: March 30, 2026, 8:24 p.m.