Triple

T27330652
Position Surface form Disambiguated ID Type / Status
Subject Ballyhaunis E689788 entity
Predicate hasRailwayStation P918 FINISHED
Object Ballyhaunis railway station
Ballyhaunis railway station is a regional rail stop in County Mayo, Ireland, serving the town of Ballyhaunis on the Dublin–Westport/Ballina railway line.
E1773174 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: Ballyhaunis railway station | Statement: [Ballyhaunis, hasRailwayStation, Ballyhaunis railway station]
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: Ballyhaunis railway station
Triple: [Ballyhaunis, hasRailwayStation, Ballyhaunis railway station]
Generated description
Ballyhaunis railway station is a regional rail stop in County Mayo, Ireland, serving the town of Ballyhaunis on the Dublin–Westport/Ballina railway line.

Provenance (5 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_69ef355d4cb08190ab032c0a2e7d3753 completed April 27, 2026, 10:07 a.m.
NER Named-entity recognition batch_69f62acb65fc8190848dbe87124811ae completed May 2, 2026, 4:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a12b22ec96c8190a07ada27ccfe78f9 completed May 24, 2026, 8:09 a.m.
NEDg Description generation batch_6a12b4bb7f5481908290eefad23b73db completed May 24, 2026, 8:20 a.m.
NED2 Entity disambiguation (via description) batch_6a12b53828688190978b1547d0753f30 completed May 24, 2026, 8:22 a.m.
Created at: April 27, 2026, 11:38 a.m.