Triple

T3910796
Position Surface form Disambiguated ID Type / Status
Subject Nuremberg City Walls E87315 entity
Predicate significantGate P24982 FINISHED
Object Laufer Tor E399009 NE 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: Laufer Tor | Statement: [Nuremberg City Walls, significantGate, Laufer Tor]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Laufer Tor
Context triple: [Nuremberg City Walls, significantGate, Laufer Tor]
  • A. Kröpeliner Tor
    Kröpeliner Tor is a historic medieval city gate and prominent architectural landmark in the German city of Rostock.
  • B. Florian Gate
    Florian Gate is a historic medieval city gate in Kraków, Poland, and one of the best-preserved remnants of the city’s old defensive walls.
  • C. Frauentor chosen
    Frauentor is a historic city gate in Nuremberg, Germany, notable as one of the main entrances through the medieval fortifications into the old town.
  • D. Erer Gate
    Erer Gate is one of the historic gateways in the ancient walled city of Harar Jugol in eastern Ethiopia.
  • E. Hallesches Tor
    Hallesches Tor is a major Berlin U-Bahn interchange station in the Kreuzberg district, serving as a key hub for multiple subway lines.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

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_69aed9424514819086e9c58adde6652d completed March 9, 2026, 2:29 p.m.
NER Named-entity recognition batch_69aef90e5f408190abf8353e153d1558 completed March 9, 2026, 4:45 p.m.
NED1 Entity disambiguation (via context triple) batch_69b5337f3ae08190ba68fc20a3ba4692 completed March 14, 2026, 10:07 a.m.
Created at: March 9, 2026, 3:22 p.m.