Triple
T5362199
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | AT&T U-verse |
E103046
|
entity |
| Predicate | hasCustomerEquipment |
P2728
|
FINISHED |
| Object | set-top box |
—
|
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: set-top box | Statement: [AT&T U-verse, hasCustomerEquipment, set-top box]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCustomerEquipment Context triple: [AT&T U-verse, hasCustomerEquipment, set-top box]
-
A.
usesEquipment
chosen
Indicates that an entity employs or operates a particular piece of equipment to perform an action or fulfill a function.
-
B.
hasCustomers
Indicates that an entity maintains a business relationship in which other entities purchase or receive its goods or services as customers.
-
C.
hasSatelliteTerminal
Indicates that an entity is equipped with or connected to a satellite communication terminal.
-
D.
hasFramingDevice
Indicates that one entity serves as a narrative or structural framing device that contextualizes, introduces, or encloses the main content of another entity.
-
E.
usedEquipmentFrom
Indicates that one entity has utilized or operated equipment that originated from or was provided by 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_69bd43daa3e4819090b59d127db70e57 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd865a0bb081909579cfe7c7974075 |
completed | March 20, 2026, 5:39 p.m. |
| PD | Predicate disambiguation | batch_69bd845f41f88190b75b8b64b9e41862 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:02 p.m.