Triple

T34509981

Position	Surface form	Disambiguated ID	Type / Status
Subject	Schlossplatz (Wiesbaden)	`E885991`	entity
Predicate	nearbyBusStop	`P15438`	FINISHED
Object	Schlossplatz bus stop Schlossplatz bus stop is a public transit stop in Wiesbaden, Germany, serving passengers visiting the central Schlossplatz square and its surrounding attractions.	`E2100279`	NE FINISHED

How this triple was built (3 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: Schlossplatz bus stop | Statement: [Schlossplatz (Wiesbaden), nearbyBusStop, Schlossplatz bus stop]

NEDg Description generation gpt-5.1

Instruction

Generate a one-sentence description of the target entity. 
You are given a context triple in the form (subject, predicate, object), where the object is the target entity. 
# Instructions
Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. 
Avoid repeating the information from the triple, unless really essential.
# Response Format
Return only the sentence: "Description: [one-sentence description of the target entity]"

Input

Entity: Schlossplatz bus stop
Triple: [Schlossplatz (Wiesbaden), nearbyBusStop, Schlossplatz bus stop]

Generated description

Schlossplatz bus stop is a public transit stop in Wiesbaden, Germany, serving passengers visiting the central Schlossplatz square and its surrounding attractions.

PD Predicate disambiguation gpt-5-mini-2025-08-07

Target predicate: nearbyBusStop
Context triple: [Schlossplatz (Wiesbaden), nearbyBusStop, Schlossplatz bus stop]

A. nearbyHeritageStation
Indicates that one entity is located close to a heritage (historically or culturally significant) station.
B. nearbyTerminus
Indicates that one terminus (end point or final stop) is located close to another terminus in space.
C. 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.
D. hasNearbyTramStop
Indicates that a location has a tram stop situated within a short walking distance or close proximity.
E. nearbyLRTStation
Indicates that there is an LRT (light rail transit) station located close to the referenced place or entity.
F. None of above.

Provenance (6 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_69f349cc0220819081f154c6964f4dc2`	completed	April 30, 2026, 12:23 p.m.
NER	Named-entity recognition	`batch_69fe7b1c506c8190869c1a22031e0571`	completed	May 9, 2026, 12:09 a.m.
NED1	Entity disambiguation (via context triple)	`batch_6a3729db72b881909fa25536459d04e0`	completed	June 21, 2026, 12:01 a.m.
NEDg	Description generation	`batch_6a372a47f6a88190af8922a3af8c5eba`	completed	June 21, 2026, 12:03 a.m.
NED2	Entity disambiguation (via description)	`batch_6a372acf6ce48190bec089a269da1194`	completed	June 21, 2026, 12:05 a.m.
PD	Predicate disambiguation	`batch_69fe796b2bdc8190a86980d44008f875`	completed	May 9, 2026, 12:01 a.m.

Created at: May 1, 2026, 2:01 a.m.