Triple
T4015680
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dracut, Massachusetts |
E90750
|
entity |
| Predicate | adjacentUrbanCenter |
P36605
|
FINISHED |
| Object | Lowell, Massachusetts |
—
|
NE NERFINISHED |
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: Lowell, Massachusetts | Statement: [Dracut, Massachusetts, adjacentUrbanCenter, Lowell, Massachusetts]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: adjacentUrbanCenter Context triple: [Dracut, Massachusetts, adjacentUrbanCenter, Lowell, Massachusetts]
-
A.
nearbyUrbanCenter
chosen
Indicates that one location is geographically close to an urban center, such as a city or large town.
-
B.
hasNearestLargerSettlement
Indicates that one settlement is associated with the geographically closest settlement that is larger in size or population.
-
C.
hasUrbanProximity
Indicates that one entity is located near or within easy access to an urban area associated with another entity.
-
D.
administrativeCentreNearby
Indicates that an administrative centre is located close to the referenced entity in geographic or spatial terms.
-
E.
regionCapitalNearby
Indicates that a capital city of a region is located close to the referenced place or entity.
- 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_69aed95e44088190aff7d90a151b1b20 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aefaec08dc8190a341809059554f84 |
completed | March 9, 2026, 4:53 p.m. |
| PD | Predicate disambiguation | batch_69aef8fa6fec81909b1190ecbba61410 |
completed | March 9, 2026, 4:44 p.m. |
Created at: March 9, 2026, 3:35 p.m.