Triple
T37168716
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Central Chidlom |
E920854
|
entity |
| Predicate | hasCosmeticsSection |
P100026
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Central Chidlom, hasCosmeticsSection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCosmeticsSection Context triple: [Central Chidlom, hasCosmeticsSection, yes]
-
A.
hasCosmetics
Indicates that one entity possesses, uses, or is associated with cosmetic products or beauty-related items in relation to another entity or context.
-
B.
includesCosmetics
chosen
Indicates that one entity contains or encompasses cosmetic products or items as part of its contents or offerings.
-
C.
hasCosmeticUse
Indicates that something is used for cosmetic purposes, such as enhancing or altering appearance.
-
D.
hasFashionSection
Indicates that something (such as a publication, website, or store) includes a dedicated section or area focused on fashion-related content or products.
-
E.
hasTribalSections
Indicates that an entity is divided into or associated with specific tribal sections or subgroups.
- 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_69f76ea16f288190b445aa1604d996f4 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_6a037c8efcd4819088c2aeead65d93df |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 3, 2026, 4:15 p.m.