Triple
T4974301
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 10 Upper Bank Street |
E111727
|
entity |
| Predicate | hasPrimaryIndustryServed |
P13077
|
FINISHED |
| Object | legal services |
—
|
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: legal services | Statement: [10 Upper Bank Street, hasPrimaryIndustryServed, legal services]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPrimaryIndustryServed Context triple: [10 Upper Bank Street, hasPrimaryIndustryServed, legal services]
-
A.
containsIndustry
Indicates that one entity includes or encompasses a particular industry within its scope, structure, or operations.
-
B.
hasPrincipalIndustry
chosen
Indicates that an entity’s main or primary industry of operation is the specified industry.
-
C.
hasServiceSectorDominance
Indicates that the service sector constitutes the largest or most influential portion of an entity’s overall economic or operational activity.
-
D.
hasIndustrialSector
Indicates that an entity is associated with, operates in, or belongs to a particular industrial sector or branch of economic activity.
-
E.
isPartOfIndustry
Indicates that one entity belongs to, operates within, or is categorized under a particular industry sector.
- 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_69bd441a0eb481908050fa4273b19eae |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd730a7590819088ab8d49c5c88c2f |
completed | March 20, 2026, 4:17 p.m. |
| PD | Predicate disambiguation | batch_69bd7146e6e881908a55ab2756b631f6 |
completed | March 20, 2026, 4:09 p.m. |
Created at: March 20, 2026, 1:33 p.m.