Triple
T23622332
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Town of Central, South Carolina |
E583353
|
entity |
| Predicate | distanceToClemsonUniversity |
P153311
|
FINISHED |
| Object | approximately 5 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: approximately 5 miles | Statement: [Town of Central, South Carolina, distanceToClemsonUniversity, approximately 5 miles]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToClemsonUniversity Context triple: [Town of Central, South Carolina, distanceToClemsonUniversity, approximately 5 miles]
-
A.
distanceToMorgantownMi
Indicates the measured distance from a given entity or location to Morgantown, Michigan.
-
B.
distanceToCharlestonMi
Indicates the measured distance, in miles, from a given entity or location to Charleston.
-
C.
distanceToWinstonSalem
Indicates the spatial distance between a given entity’s location and the city of Winston-Salem.
-
D.
distanceToCharlotte
Indicates the measured or estimated distance between a given entity and the location Charlotte.
-
E.
distanceToRichmond
Indicates the measured distance between a given location or entity and the place named Richmond.
- 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_69e248fc8d74819091bd5baef2f36f6f |
completed | April 17, 2026, 2:51 p.m. |
| NER | Named-entity recognition | batch_69f1b179ebf48190a34ad0d3ddf0e103 |
completed | April 29, 2026, 7:21 a.m. |
| PD | Predicate disambiguation | batch_69f118d0e0588190a86527a7747c5427 |
completed | April 28, 2026, 8:30 p.m. |
| PDg | Predicate description generation | batch_69f138b8c9248190b059bc38a9a50958 |
completed | April 28, 2026, 10:46 p.m. |
Created at: April 17, 2026, 6:46 p.m.