Triple
T1090409
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Plymouth, Massachusetts |
E24148
|
entity |
| Predicate | distanceToBostonMiles |
P798
|
FINISHED |
| Object | approximately 40 |
—
|
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 40 | Statement: [Plymouth, Massachusetts, distanceToBostonMiles, approximately 40]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: distanceToBostonMiles Context triple: [Plymouth, Massachusetts, distanceToBostonMiles, approximately 40]
-
A.
distanceFromBoston
chosen
Indicates the spatial distance between a given entity’s location and the city of Boston.
-
B.
distanceToNewYorkCity
Indicates the spatial distance between a given entity’s location and New York City.
-
C.
distanceToPhiladelphia
Indicates the spatial distance between a given entity’s location and the city of Philadelphia.
-
D.
distanceToBangorMaine
Indicates the spatial distance between a given entity or location and Bangor, Maine.
-
E.
distanceToWashingtonDC
Indicates the physical distance between a given location and Washington, D.C.
- F. None of above.
Provenance (3 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_69a49404428c819092dcc9632f5f7b8b |
completed | March 1, 2026, 7:31 p.m. |
| NER | Named-entity recognition | batch_69a4b980c8448190b08c3a9a7e7f4e85 |
completed | March 1, 2026, 10:11 p.m. |
| PD | Predicate disambiguation | batch_69a4b741b0cc8190be001a16a81f6d9e |
completed | March 1, 2026, 10:01 p.m. |
Created at: March 1, 2026, 7:42 p.m.