Triple
T18656751
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymondville, New York |
E456084
|
entity |
| Predicate | distanceToPotsdamInMiles |
P132176
|
FINISHED |
| Object | approximately 16 |
—
|
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 16 | Statement: [Raymondville, New York, distanceToPotsdamInMiles, approximately 16]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToPotsdamInMiles Context triple: [Raymondville, New York, distanceToPotsdamInMiles, approximately 16]
-
A.
distanceToPetersburgInMiles
Indicates the numerical distance, measured in miles, between a given entity’s location and Petersburg.
-
B.
distanceToDresden
Indicates the spatial distance between a given entity or location and the city of Dresden.
-
C.
distanceToBerlin
Indicates the spatial distance between a given entity’s location and the city of Berlin.
-
D.
distanceToMunich
Indicates the spatial distance between a given entity’s location and the city of Munich.
-
E.
distanceToBaltimoreInMiles
Indicates the numerical distance, measured in miles, between a given location and the city of Baltimore.
- 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_69d8d38ea1e88190997e9b231190ba6f |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e55084ca3481909ff3fd9045f25dcd |
completed | April 19, 2026, 10 p.m. |
| PD | Predicate disambiguation | batch_69e478d85864819093cbad5ed9b54878 |
completed | April 19, 2026, 6:40 a.m. |
| PDg | Predicate description generation | batch_69e484133ee48190a80f1889d79f34c9 |
completed | April 19, 2026, 7:28 a.m. |
Created at: April 10, 2026, 11:47 a.m.