Triple
T10866108
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Harrods |
E256532
|
entity |
| Predicate | hasDepartment |
P35
|
FINISHED |
| Object | Harrods Home |
E256532
|
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: Harrods Home | Statement: [Harrods, hasDepartment, Harrods Home]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Harrods Home Context triple: [Harrods, hasDepartment, Harrods Home]
-
A.
Hammerson
Hammerson is a major British property development and investment company specializing in retail destinations such as shopping centres and retail parks.
-
B.
Harrods
chosen
Harrods is a world-famous luxury department store in London renowned for its upscale shopping, elaborate food halls, and iconic Knightsbridge location.
-
C.
Hamleys
Hamleys is a world-famous British toy store chain best known for its flagship multi-storey shop in central London.
-
D.
Harvey Nichols
Harvey Nichols is a luxury British department store renowned for its high-end fashion, beauty, and lifestyle offerings.
-
E.
Debenhams
Debenhams was a major British department store chain offering fashion, beauty, and home goods through high-street locations and online retail.
- 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_69d6aa83d1448190a66d93c32394d21f |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d7516cebe881909ed358a7641f6a12 |
completed | April 9, 2026, 7:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69dff7d7b32081909dd5f8ae3fe293be |
completed | April 15, 2026, 8:40 p.m. |
Created at: April 8, 2026, 9:20 p.m.