Triple
T11833569
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Slough Trading Estate |
E281457
|
entity |
| Predicate | numberOfBusinesses |
P17464
|
FINISHED |
| Object | over 400 |
—
|
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: over 400 | Statement: [Slough Trading Estate, numberOfBusinesses, over 400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBusinesses Context triple: [Slough Trading Estate, numberOfBusinesses, over 400]
-
A.
numberOfRestaurantsAndRetail
Indicates the total count of entities that are either restaurants or retail establishments associated with a given subject.
-
B.
hasNumberOfCompanies
chosen
Indicates the quantitative relationship specifying how many companies are associated with a given entity.
-
C.
numberOfRestaurants
Indicates the quantitative count of restaurants associated with a given entity or context.
-
D.
numberOfVenues
Indicates the total count of venues associated with a given entity or context.
-
E.
businessBase
Indicates that one entity serves as the primary business foundation, core location, or main operational base for another entity.
- 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_69d6ab276f8c8190b1966a0ef11349ac |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d8a62e7e408190998bebe346c82e89 |
completed | April 10, 2026, 7:26 a.m. |
| PD | Predicate disambiguation | batch_69d8a251fc08819095933f1d13c3b742 |
completed | April 10, 2026, 7:10 a.m. |
Created at: April 8, 2026, 9:43 p.m.