Triple
T8462418
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Line 1 (Shanghai Metro) |
E200073
|
entity |
| Predicate | hasPlatformScreenDoorsOnMostStations |
P22114
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Line 1 (Shanghai Metro), hasPlatformScreenDoorsOnMostStations, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasPlatformScreenDoorsOnMostStations Context triple: [Line 1 (Shanghai Metro), hasPlatformScreenDoorsOnMostStations, true]
-
A.
hasPlatformScreenDoors
chosen
Indicates that a transit station or platform is equipped with platform screen doors separating passengers from the tracks.
-
B.
hasPassengerShelterOnEachPlatform
Indicates that every platform at a given location is equipped with a passenger shelter.
-
C.
hasRailPlatforms
Indicates that an entity is equipped with one or more rail platforms used for boarding or alighting from trains.
-
D.
hasDepartureScreens
Indicates that a location or facility is equipped with screens displaying departure information for services such as trains, buses, or flights.
-
E.
hasSubwayStationEntrance
Indicates that one entity serves as an entrance or access point to a subway station associated with 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_69ca83198c4c8190a337bf717d1813f5 |
completed | March 30, 2026, 2:05 p.m. |
| NER | Named-entity recognition | batch_69cbe4a251f08190840a7fc31ff528b5 |
completed | March 31, 2026, 3:13 p.m. |
| PD | Predicate disambiguation | batch_69cbd0fc634481909842c0a30077bfde |
completed | March 31, 2026, 1:49 p.m. |
Created at: March 30, 2026, 6:10 p.m.