Triple
T21752645
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deer Park |
E536951
|
entity |
| Predicate | hasMarketScope |
P59415
|
FINISHED |
| Object | regional |
—
|
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: regional | Statement: [Deer Park, hasMarketScope, regional]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMarketScope Context triple: [Deer Park, hasMarketScope, regional]
-
A.
hasMarket
Indicates that an entity possesses, operates in, or is associated with a particular market or marketplace.
-
B.
hasMarketFocus
Indicates that an entity concentrates its business activities, products, or services on a particular market or customer segment.
-
C.
hasGlobalMarketShare
Indicates that an entity possesses a specified proportion of sales or presence in the worldwide market relative to all competitors.
-
D.
hasMarketingRegion
chosen
Indicates that an entity is associated with or assigned to a specific marketing region for targeting, management, or analysis purposes.
-
E.
hasMarketIndex
Indicates that an entity is associated with, or tracked by, a specific market index.
- 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_69e0c46eab808190b848242d63a17c47 |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69f01d8b8b9c8190b1f6a8bc25d69dbb |
completed | April 28, 2026, 2:38 a.m. |
| PD | Predicate disambiguation | batch_69e6969c16fc8190b5126c169317d85d |
completed | April 20, 2026, 9:11 p.m. |
Created at: April 16, 2026, 6:50 p.m.