Triple
T4830673
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin Franklin's grave |
E107935
|
entity |
| Predicate | hasViewThrough |
P59914
|
FINISHED |
| Object | iron fence along Arch Street |
—
|
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: iron fence along Arch Street | Statement: [Benjamin Franklin's grave, hasViewThrough, iron fence along Arch Street]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasViewThrough Context triple: [Benjamin Franklin's grave, hasViewThrough, iron fence along Arch Street]
-
A.
hasView
Indicates that one entity provides a visual perspective or outlook onto another entity or scene.
-
B.
hasSee
Indicates that one entity has perceived or visually observed another entity.
-
C.
hasViewingSide
Indicates that one entity serves as the side or surface of another entity that is intended to be viewed or observed.
-
D.
viewedBySomeAs
Indicates that at least one observer or group perceives or interprets an entity in a particular way or role.
-
E.
viewedBy
Indicates that something has been seen, observed, or watched by a particular entity.
- 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_69bd43fac8188190803f0327190621e4 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd6ddd17d881909f7731ff2b460e83 |
completed | March 20, 2026, 3:55 p.m. |
| PD | Predicate disambiguation | batch_69bd6c1fe130819087ae01309f96a0c8 |
completed | March 20, 2026, 3:47 p.m. |
| PDg | Predicate description generation | batch_69bd6dda5e808190a26ec85e4499d8e4 |
completed | March 20, 2026, 3:55 p.m. |
Created at: March 20, 2026, 1:24 p.m.