Triple
T9659300
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | H&M |
E233546
|
entity |
| Predicate | hasBrand |
P1500
|
FINISHED |
| Object | H&M Home |
E233546
|
NE 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: H&M Home | Statement: [H&M, hasBrand, H&M Home]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: H&M Home Context triple: [H&M, hasBrand, H&M Home]
-
A.
IKEA
IKEA is a multinational Swedish-founded retailer known for its affordable, flat-pack furniture, home goods, and large warehouse-style stores worldwide.
-
B.
Etro
Etro is an Italian luxury fashion house renowned for its vibrant prints, paisley patterns, and eclectic, bohemian-inspired designs.
-
C.
H&M
chosen
H&M is a global fast-fashion retail chain known for offering trendy clothing and accessories at affordable prices.
-
D.
H&M
H&M, in this context, refers to the historic Hudson and Manhattan Railroad, an early 20th-century rapid transit system that connected Manhattan with New Jersey and served as a predecessor to today’s PATH trains.
-
E.
Hammerson
Hammerson is a major British property development and investment company specializing in retail destinations such as shopping centres and retail parks.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69ca848c1ba88190b84b410cd14627fc |
completed | March 30, 2026, 2:11 p.m. |
| NER | Named-entity recognition | batch_69cd9bdfc3b08190835e86ff99663214 |
completed | April 1, 2026, 10:27 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d18a0b84a0819083191beeaf8d968b |
completed | April 4, 2026, 10 p.m. |
Created at: March 30, 2026, 8:14 p.m.