Triple
T2182376
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sherman, Texas |
E49072
|
entity |
| Predicate | distanceToOklahomaBorderApprox |
P31353
|
FINISHED |
| Object | about 10 miles |
—
|
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: about 10 miles | Statement: [Sherman, Texas, distanceToOklahomaBorderApprox, about 10 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToOklahomaBorderApprox Context triple: [Sherman, Texas, distanceToOklahomaBorderApprox, about 10 miles]
-
A.
distanceToPennsylvaniaBorder
Indicates the measured distance between a given location and the border of Pennsylvania.
-
B.
distanceFromDallas
Indicates the measured distance between a given place or entity and the city of Dallas.
-
C.
distanceToBorder
chosen
Indicates the measured or estimated spatial separation between a given entity or location and the nearest relevant border or boundary.
-
D.
approximateLengthInMiles
Indicates the estimated distance or extent of something measured in miles.
-
E.
distanceToMinneapolis
Indicates the measured distance between a given entity’s location and the city of Minneapolis.
- 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_69a88aa72d348190a9544bb5b8a4e71d |
completed | March 4, 2026, 7:40 p.m. |
| NER | Named-entity recognition | batch_69abc4358fc88190a6f556c2de9fef8c |
completed | March 7, 2026, 6:22 a.m. |
| PD | Predicate disambiguation | batch_69abbda0ec948190be88c1243d81a423 |
completed | March 7, 2026, 5:54 a.m. |
Created at: March 4, 2026, 7:45 p.m.