Triple
T4417448
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Benjamin Franklin National Memorial statue (Philadelphia) |
E95008
|
entity |
| Predicate | hasSeatingPose |
P55537
|
FINISHED |
| Object | seated figure |
—
|
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: seated figure | Statement: [Benjamin Franklin National Memorial statue (Philadelphia), hasSeatingPose, seated figure]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasSeatingPose Context triple: [Benjamin Franklin National Memorial statue (Philadelphia), hasSeatingPose, seated figure]
-
A.
hasSeating
Indicates that one entity provides or contains seating capacity or seating arrangements for another entity.
-
B.
hasSeat
Indicates that one entity possesses, provides, or includes a seat for another entity.
-
C.
seatingPosition
Indicates the relative location or arrangement of an entity’s seat with respect to other seats or a reference point in a seating layout.
-
D.
hasSeatStatus
Indicates the current condition or availability state of a seat in a given context.
-
E.
hasSeatAt
Indicates that an entity occupies or holds a place, position, or membership within a specific group, body, or location.
- 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_69b3453a36908190b95a79a297ca083c |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3551d5d7481908528c2de0a6fda06 |
completed | March 13, 2026, 12:06 a.m. |
| PD | Predicate disambiguation | batch_69b34f5d0c54819085c08533bb58030a |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b34ff7018c81908ad8597e525c042b |
completed | March 12, 2026, 11:44 p.m. |
Created at: March 12, 2026, 11:29 p.m.