Triple
T18656750
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Raymondville, New York |
E456084
|
entity |
| Predicate | distanceToMassenaInMiles |
P132175
|
FINISHED |
| Object | approximately 8 |
—
|
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 8 | Statement: [Raymondville, New York, distanceToMassenaInMiles, approximately 8]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToMassenaInMiles Context triple: [Raymondville, New York, distanceToMassenaInMiles, approximately 8]
-
A.
distanceToCantonInMiles
Indicates the physical separation between an entity and a specified canton, measured in miles.
-
B.
distanceToMonroe
Indicates the measured distance between a given entity and the location named Monroe.
-
C.
distance to Midtown Manhattan (miles)
Indicates the physical separation between a location and Midtown Manhattan, measured in miles.
-
D.
distanceToMarquetteInMiles
Indicates the numerical distance, measured in miles, between a given entity’s location and Marquette.
-
E.
distanceToDetroit
Indicates the measured or calculated spatial distance between a given entity and the location of Detroit.
- 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.