Triple
T948391
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Philadelphia City Hall |
E20463
|
entity |
| Predicate | hasUndergroundTransitConnection |
P15438
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Philadelphia City Hall, hasUndergroundTransitConnection, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUndergroundTransitConnection Context triple: [Philadelphia City Hall, hasUndergroundTransitConnection, yes]
-
A.
hasPublicTransportConnection
Indicates that there is an available public transportation link or service connecting the related entities.
-
B.
hasPublicTransitProvider
Indicates that a place or region is served by a specific public transit operating organization or agency.
-
C.
hasUndergroundSection
Indicates that an entity includes a portion or segment that is located below ground level.
-
D.
hasTransportHub
Indicates that a location contains or serves as a central facility where multiple transport routes or modes connect for passenger or cargo movement.
-
E.
hasPublicTransportStop
chosen
Indicates that a location or area contains or is served by a public transport stop, such as a bus, tram, or train stop.
- 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_69a493b0f2fc81908cd227480a5356a1 |
completed | March 1, 2026, 7:29 p.m. |
| NER | Named-entity recognition | batch_69a4b3bf9bb88190a79b2db698613a8d |
completed | March 1, 2026, 9:46 p.m. |
| PD | Predicate disambiguation | batch_69a4b29f05f481908814bd11f235e9d0 |
completed | March 1, 2026, 9:41 p.m. |
Created at: March 1, 2026, 7:40 p.m.