Triple
T2973048
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bedford, Massachusetts |
E80325
|
entity |
| Predicate | hasRevolutionaryWarHeritage |
P4345
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Bedford, Massachusetts, hasRevolutionaryWarHeritage, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRevolutionaryWarHeritage Context triple: [Bedford, Massachusetts, hasRevolutionaryWarHeritage, true]
-
A.
hasMilitarySignificanceSince
Indicates that something has held military importance or strategic value starting from a specified point in time.
-
B.
hasNearbyMilitaryHistorySite
Indicates that an entity is located close to a site of historical military significance, such as a battlefield, fort, or memorial.
-
C.
hasHistoricalSignificance
chosen
Indicates that something possesses notable importance or influence within a historical context or period.
-
D.
hasMilitarySignificance
Indicates that something holds strategic or tactical importance for military planning, operations, or defense objectives.
-
E.
hasColonialHistoryWith
Indicates that one entity has a historical relationship of colonization or being colonized involving the other 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_69ad8b14ffe881908ffed62f9595c867 |
completed | March 8, 2026, 2:43 p.m. |
| NER | Named-entity recognition | batch_69ad9987bb6c8190adfb447b76276962 |
completed | March 8, 2026, 3:45 p.m. |
| PD | Predicate disambiguation | batch_69ad96105a708190a9ec4838cbcb1207 |
completed | March 8, 2026, 3:30 p.m. |
Created at: March 8, 2026, 2:58 p.m.