Triple
T22298277
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Goodyear |
E551180
|
entity |
| Predicate | hasMajorHighway |
P385
|
FINISHED |
| Object | Loop 303 |
—
|
NE NERFINISHED |
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: Loop 303 | Statement: [Goodyear, hasMajorHighway, Loop 303]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Loop 303 Context triple: [Goodyear, hasMajorHighway, Loop 303]
-
A.
Loop 303
chosen
Loop 303 is a major freeway in the Phoenix metropolitan area that serves as part of the region’s outer beltway system, facilitating circumferential travel and suburban growth.
-
B.
Loop 323
Loop 323 is a primary circumferential highway that serves as the main loop route around the city of Tyler, Texas.
-
C.
Loop 336
Loop 336 is a major circumferential roadway that serves as a key traffic artery around the city of Conroe, Texas.
-
D.
Loop 286
Loop 286 is a state highway loop that serves as a beltway around the city of Paris in Lamar County, Texas.
-
E.
Loop 1604
Loop 1604 is a major highway encircling much of San Antonio, Texas, serving as a key route for regional traffic and access to suburban districts and commercial areas.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69e11e45fb848190a1b2ae21296e3a5f |
completed | April 16, 2026, 5:37 p.m. |
| NER | Named-entity recognition | batch_69f1572200c88190b9413286136fef15 |
completed | April 29, 2026, 12:56 a.m. |
Created at: April 16, 2026, 8:41 p.m.