Triple

T31291144
Position Surface form Disambiguated ID Type / Status
Subject Great South Wall E797943 entity
Predicate locatedNear P294 FINISHED
Object Pigeon House Road
Pigeon House Road is a coastal roadway in Dublin, Ireland, running through the city’s docklands area near the historic Pigeon House power station and Great South Wall.
E2294347 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: Pigeon House Road | Statement: [Great South Wall, locatedNear, Pigeon House Road]
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: Pigeon House Road
Triple: [Great South Wall, locatedNear, Pigeon House Road]
Generated description
Pigeon House Road is a coastal roadway in Dublin, Ireland, running through the city’s docklands area near the historic Pigeon House power station and Great South Wall.

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_69f224dfde288190af313f3c221c857e completed April 29, 2026, 3:33 p.m.
NER Named-entity recognition batch_69f69e2c79f481908e90edba6907fc69 completed May 3, 2026, 1 a.m.
NED1 Entity disambiguation (via context triple) batch_6a7bd8a8f6e081909c7b1258c490f6e2 completed Aug. 12, 2026, 2:21 a.m.
NEDg Description generation batch_6a7bda8b6de88190b83376b09287dcba completed Aug. 12, 2026, 2:29 a.m.
NED2 Entity disambiguation (via description) batch_6a7bdafbc55481909222062676409547 completed Aug. 12, 2026, 2:31 a.m.
Created at: April 29, 2026, 9:14 p.m.