Triple
T142325
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Littleton, Massachusetts |
E2879
|
entity |
| Predicate | hasFormOfSettlement |
P1068
|
FINISHED |
| Object | suburban town |
—
|
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: suburban town | Statement: [Littleton, Massachusetts, hasFormOfSettlement, suburban town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormOfSettlement Context triple: [Littleton, Massachusetts, hasFormOfSettlement, suburban town]
-
A.
settlementType
chosen
Indicates the specific kind or category of human settlement an entity represents, such as a city, village, town, or hamlet.
-
B.
settlementPattern
Indicates how human dwellings or communities are spatially arranged and distributed across a geographic area.
-
C.
servesSettlement
Indicates that one entity provides services or support to a particular settlement or community.
-
D.
supportsAddressTypes
Indicates that an entity is capable of handling or working with one or more specified types of addresses.
-
E.
hasBank
Indicates that one entity possesses, is associated with, or is served by a particular bank (such as a financial institution or river bank).
- 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_69a2521e35c08190b28e5c9f1e3c9b59 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a2580ca15481909fa3e87d804a1b23 |
completed | Feb. 28, 2026, 2:50 a.m. |
| PD | Predicate disambiguation | batch_69a2565559ac81909e0c4e095a7dfa27 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:31 a.m.