Triple
T10686910
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tioga, Texas |
E251900
|
entity |
| Predicate | distanceToOklahomaBorderInMiles |
P95308
|
FINISHED |
| Object | approximately 25 |
—
|
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: approximately 25 | Statement: [Tioga, Texas, distanceToOklahomaBorderInMiles, approximately 25]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToOklahomaBorderInMiles Context triple: [Tioga, Texas, distanceToOklahomaBorderInMiles, approximately 25]
-
A.
distanceToOklahomaCity
Indicates the spatial distance between a given entity’s location and the location of Oklahoma City.
-
B.
distanceToMexicoBorder
Indicates the measured or estimated distance between a given location or entity and the border of Mexico.
-
C.
distanceToWichita
Indicates the measured distance between a given entity’s location and the city of Wichita.
-
D.
distanceToTulsa
Indicates the spatial distance between a given entity’s location and the city of Tulsa.
-
E.
distanceToOmaha
Indicates the spatial distance between a given entity’s location and the location of Omaha.
- 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_69d6aa5bd7c08190a816e733b4045c23 |
completed | April 8, 2026, 7:19 p.m. |
| NER | Named-entity recognition | batch_69d6fd192220819088eff88148376266 |
completed | April 9, 2026, 1:12 a.m. |
| PD | Predicate disambiguation | batch_69d6dd8cc0788190b4c02a772e4b58b3 |
completed | April 8, 2026, 10:58 p.m. |
| PDg | Predicate description generation | batch_69d6df47899481909ac0e518d94883cb |
completed | April 8, 2026, 11:05 p.m. |
Created at: April 8, 2026, 9:10 p.m.