Triple
T10849111
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | TxTag |
E256092
|
entity |
| Predicate | compatibleWith |
P203
|
FINISHED |
| Object | EZ TAG |
E256093
|
NE 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: EZ TAG | Statement: [TxTag, compatibleWith, EZ TAG]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: EZ TAG Context triple: [TxTag, compatibleWith, EZ TAG]
-
A.
EZ TAG
chosen
EZ TAG is an electronic toll collection system used on certain Texas toll roads that allows drivers to pay tolls automatically without stopping.
-
B.
K-TAG
K-TAG is an electronic toll collection system used on the Kansas Turnpike and compatible highways, allowing drivers to pay tolls automatically via a windshield-mounted transponder.
-
C.
TollTag
TollTag is an electronic toll collection system used on North Texas toll roads, allowing drivers to pay tolls automatically without stopping.
-
D.
TxTag
TxTag is an electronic toll collection system used on Texas toll roads that allows drivers to pay tolls automatically without stopping.
-
E.
ATAG
ATAG (Authoring Tool Accessibility Guidelines) is a W3C specification that defines how software used to create web content should support accessibility both in its user interface and in the content it produces.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d75115e4a88190b77be46b63db0c84 |
completed | April 9, 2026, 7:11 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69deb170e714819097babb2b850342d2 |
completed | April 14, 2026, 9:28 p.m. |
Created at: April 8, 2026, 9:20 p.m.