Triple
T37245003
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lehigh Acres, Florida |
E923822
|
entity |
| Predicate | distanceToFortMyers |
P205792
|
FINISHED |
| Object | approximately 15 miles east |
—
|
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 15 miles east | Statement: [Lehigh Acres, Florida, distanceToFortMyers, approximately 15 miles east]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToFortMyers Context triple: [Lehigh Acres, Florida, distanceToFortMyers, approximately 15 miles east]
-
A.
distanceFromMiami
Indicates the spatial distance between a given entity’s location and the city of Miami.
-
B.
distanceToFlorida
Indicates the spatial distance between a given entity’s location and the state of Florida.
-
C.
distanceToDaytonaBeach
Indicates the spatial distance between a given location or entity and Daytona Beach.
-
D.
distanceFromKeyWest
Indicates the measured spatial distance between a given entity or location and Key West.
-
E.
distanceFromOrlando
Indicates the measured spatial distance between a given place or object and the location of Orlando.
- 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_69f76eaabb4c819093b751b139dad551 |
completed | May 3, 2026, 3:50 p.m. |
| NER | Named-entity recognition | batch_6a037cad051c8190b28b354b89208574 |
completed | May 12, 2026, 7:17 p.m. |
| PD | Predicate disambiguation | batch_6a037a11efc08190bb7cacc1325b4dc6 |
completed | May 12, 2026, 7:05 p.m. |
| PDg | Predicate description generation | batch_6a037c842b2c819082f1d2db995ac2eb |
completed | May 12, 2026, 7:16 p.m. |
Created at: May 3, 2026, 4:15 p.m.