Triple
T363698
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | PENN Entertainment |
E7911
|
entity |
| Predicate | hasPhysicalFootprint |
P12400
|
FINISHED |
| Object | brick-and-mortar casinos |
—
|
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: brick-and-mortar casinos | Statement: [PENN Entertainment, hasPhysicalFootprint, brick-and-mortar casinos]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPhysicalFootprint Context triple: [PENN Entertainment, hasPhysicalFootprint, brick-and-mortar casinos]
-
A.
hasSettlementAtFoot
Indicates that a settlement is located at the base or lower slopes of a geographic feature such as a hill or mountain.
-
B.
hasFormFactor
Indicates that one entity possesses or is characterized by a particular physical or structural form factor defined by another entity.
-
C.
hasPowerSource
Indicates that an entity derives its operational energy or functionality from a specified power source.
-
D.
hasCP
Indicates that an entity possesses, is associated with, or is characterized by a specific CP (such as a control point, contact person, or configuration parameter), depending on the domain context.
-
E.
hasUSBPort
Indicates that one entity is equipped with or includes a USB port available for connection or data/power transfer.
- F. None of above. chosen
Provenance (4 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_69a2e7e880008190a6ad7e06e5d03007 |
completed | Feb. 28, 2026, 1:04 p.m. |
| NER | Named-entity recognition | batch_69a2ebd1016481909b8ba3b047a47145 |
completed | Feb. 28, 2026, 1:21 p.m. |
| PD | Predicate disambiguation | batch_69a2e95c843c8190b2aba9af6e869ba1 |
completed | Feb. 28, 2026, 1:10 p.m. |
| PDg | Predicate description generation | batch_69a2ea2c44408190946267525c88e811 |
completed | Feb. 28, 2026, 1:14 p.m. |
Created at: Feb. 28, 2026, 1:08 p.m.