Triple
T30556922
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Franklin, Massachusetts |
E777722
|
entity |
| Predicate | hasHistoricCollection |
P195453
|
FINISHED |
| Object | books donated by Benjamin Franklin |
—
|
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: books donated by Benjamin Franklin | Statement: [Franklin, Massachusetts, hasHistoricCollection, books donated by Benjamin Franklin]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricCollection Context triple: [Franklin, Massachusetts, hasHistoricCollection, books donated by Benjamin Franklin]
-
A.
hasHistoricProperty
Indicates that one entity possesses, contains, or is associated with a property that has historical significance or heritage value.
-
B.
hasHistoricMP
Indicates that an entity is or has been represented by a specific Member of Parliament at some point in the past.
-
C.
hasHistoryIn
Indicates that an entity has a past involvement, presence, or record of activity within a particular domain, context, or location.
-
D.
hasHistoricType
Indicates that an entity is associated with a specific historical classification, category, or type it held in the past.
-
E.
isHistoricFor
Indicates that something has historical significance, relevance, or impact specifically in relation to a given entity or context.
- F. None of above. chosen
Provenance (4 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_69f2249ed41c8190b175170ecfd6e1c5 |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fdd2be648c8190b60b3d1caeb44364 |
completed | May 8, 2026, 12:10 p.m. |
| PD | Predicate disambiguation | batch_69fdd14a5c708190a6f95ec61f4fc28f |
completed | May 8, 2026, 12:04 p.m. |
| PDg | Predicate description generation | batch_69fdd2bda90881909aa229194d014ba7 |
completed | May 8, 2026, 12:10 p.m. |
Created at: April 29, 2026, 8:20 p.m.