Triple
T2499698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Regent Street |
E52433
|
entity |
| Predicate | hasTenant |
P3277
|
FINISHED |
| Object | H&M |
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 | Statement: [Regent Street, hasTenant, H&M]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: H&M Context triple: [Regent Street, hasTenant, H&M]
-
A.
H&M
chosen
H&M is a global fast-fashion retail chain known for offering trendy clothing and accessories at affordable prices.
-
B.
Zara
Zara is the historical Italian name for the coastal Croatian city of Zadar on the Adriatic Sea.
-
C.
Uniqlo
Uniqlo is a global Japanese clothing retailer known for its affordable, minimalist casual wear and functional basics.
-
D.
Primark
Primark is a major Irish-founded fast-fashion retail chain known for its low-priced clothing, accessories, and home goods, operating under the Penneys brand in Ireland and Primark elsewhere in Europe and the United States.
-
E.
Marshalls
Marshalls is a major American off-price department store chain known for selling brand-name clothing, home goods, and accessories at discounted prices.
- 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_69ab4957b3a88190adf968ae0c1b931c |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abd1afd86c81909181c4b45d4f8bc5 |
completed | March 7, 2026, 7:20 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69af1f9ed13c81909856db636bfb2e9e |
completed | March 9, 2026, 7:29 p.m. |
Created at: March 6, 2026, 9:46 p.m.