Triple
T105176
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Schuylkill River Trail |
E2122
|
entity |
| Predicate | hasAccessPoint |
P1985
|
FINISHED |
| Object | Philadelphia Museum of Art area |
—
|
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: Philadelphia Museum of Art area | Statement: [Schuylkill River Trail, hasAccessPoint, Philadelphia Museum of Art area]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAccessPoint Context triple: [Schuylkill River Trail, hasAccessPoint, Philadelphia Museum of Art area]
-
A.
hasAccessTo
Indicates that one entity is permitted to enter, use, or interact with another entity, resource, or location.
-
B.
accessibleFrom
chosen
Indicates that one entity can be reached, entered, or used starting from another entity, typically without obstruction.
-
C.
hasHelpPoint
Indicates that one entity provides or contains a designated help or assistance point for another entity.
-
D.
hasAddress
Indicates that an entity is associated with a specific address or location.
-
E.
hasEntranceOn
Indicates that one entity’s entrance or access point is located on or faces a specified side, boundary, or feature of another 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_69a24e0a5b7c81908d52da08c60dabc4 |
completed | Feb. 28, 2026, 2:08 a.m. |
| NER | Named-entity recognition | batch_69a25711f6788190a22252ea3a3af394 |
completed | Feb. 28, 2026, 2:46 a.m. |
| PD | Predicate disambiguation | batch_69a2563be81c81908ccc5ed44edd6b8e |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:12 a.m.