Triple
T38732
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lexington, Massachusetts |
E766
|
entity |
| Predicate | hasSettlementType |
P1068
|
FINISHED |
| Object | 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: town | Statement: [Lexington, Massachusetts, hasSettlementType, town]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSettlementType Context triple: [Lexington, Massachusetts, hasSettlementType, 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.
hasTypeOfRecipient
Indicates that an entity is associated with a specific category or kind of recipient it is intended for or directed to.
-
C.
hasServiceType
Indicates that an entity is associated with or categorized by a particular type of service.
-
D.
settled
Indicates that an entity established residence or a stable presence in a place, typically after moving from elsewhere.
-
E.
obligationType
Indicates the specific kind or category of duty, requirement, or commitment that applies within an obligation relationship.
- 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_69a247a8f6c08190bac804906d62ed5a |
completed | Feb. 28, 2026, 1:40 a.m. |
| NER | Named-entity recognition | batch_69a24b4d5bd08190a3a48eb26e67768c |
completed | Feb. 28, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69a24ab6141881908701106aa97e4735 |
completed | Feb. 28, 2026, 1:53 a.m. |
Created at: Feb. 28, 2026, 1:46 a.m.