Triple
T6090082
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Verbena, Alabama |
E135738
|
entity |
| Predicate | distanceToClanton |
P68052
|
FINISHED |
| Object | approximately 10 miles south |
—
|
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 10 miles south | Statement: [Verbena, Alabama, distanceToClanton, approximately 10 miles south]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToClanton Context triple: [Verbena, Alabama, distanceToClanton, approximately 10 miles south]
-
A.
distanceToMontgomery
Indicates the spatial distance between a given entity and the location identified as Montgomery.
-
B.
distanceToJackson
Indicates the spatial distance or separation between a given entity and Jackson.
-
C.
distanceToKnoxville
Indicates the spatial distance between a given entity’s location and the city of Knoxville.
-
D.
distanceToHuntsville
Indicates the measured distance between a given entity and the location Huntsville.
-
E.
distanceToBurford
Indicates the spatial distance between a given entity or location and the place named Burford.
- 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_69c0087bcc788190b20f093d3a6c60ec |
completed | March 22, 2026, 3:19 p.m. |
| NER | Named-entity recognition | batch_69c057a862c88190912a913973c6b6fc |
completed | March 22, 2026, 8:57 p.m. |
| PD | Predicate disambiguation | batch_69c049f3b1ec8190bea67a7bec6442a5 |
completed | March 22, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69c04e8e3f2c8190be459ca02f9b315a |
completed | March 22, 2026, 8:18 p.m. |
Created at: March 22, 2026, 4:12 p.m.