Triple

T38400596
Position Surface form Disambiguated ID Type / Status
Subject Montgomery’s Tavern E900885 entity
Predicate hasAlternateName P39 FINISHED
Object Montgomery’s Inn (historical usage in some sources) E536428 NE FINISHED

How this triple was built (1 step)

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: Montgomery’s Inn (historical usage in some sources) | Statement: [Montgomery’s Tavern, hasAlternateName, Montgomery’s Inn (historical usage in some sources)]

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_69f76e6071a081909eea7a670d21420c completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69fccd41d9b8819099bc21036b19c7a2 completed May 7, 2026, 5:34 p.m.
NED1 Entity disambiguation (via context triple) batch_6a41b2b8ab208190b55ab462d083acce completed June 28, 2026, 11:48 p.m.
Created at: May 3, 2026, 4:31 p.m.