Triple

T36567686
Position Surface form Disambiguated ID Type / Status
Subject Margate Harbour E902022 entity
Predicate hasPart P35 FINISHED
Object Margate Harbour Arm
Margate Harbour Arm is a historic stone pier and breakwater in Margate, Kent, that shelters the town’s harbour and serves as a popular promenade with views over the North Sea.
E902022 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: Margate Harbour Arm | Statement: [Margate Harbour, hasPart, Margate Harbour Arm]
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: Margate Harbour Arm
Triple: [Margate Harbour, hasPart, Margate Harbour Arm]
Generated description
Margate Harbour Arm is a historic stone pier and breakwater in Margate, Kent, that shelters the town’s harbour and serves as a popular promenade with views over the North Sea.

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_69f76e6416708190a9754b8c52d4e453 completed May 3, 2026, 3:48 p.m.
NER Named-entity recognition batch_69f7c29e1b848190b945c6c6120a5330 completed May 3, 2026, 9:48 p.m.
NED1 Entity disambiguation (via context triple) batch_6a39e6f86a2881908e83d030af707303 completed June 23, 2026, 1:52 a.m.
NEDg Description generation batch_6a39e781b60881908c02a333187588f9 completed June 23, 2026, 1:55 a.m.
NED2 Entity disambiguation (via description) batch_6a39ebb78b44819084252f4b2cefe4e6 completed June 23, 2026, 2:13 a.m.
Created at: May 3, 2026, 4:11 p.m.