Triple

T26998490
Position Surface form Disambiguated ID Type / Status
Subject Rahima Moosa Mother and Child Hospital E680039 entity
Predicate formerName P65 FINISHED
Object Coronation Hospital
Coronation Hospital was a major public healthcare facility in Johannesburg, South Africa, later renamed Rahima Moosa Mother and Child Hospital and known for serving women and children.
 E1750544 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: Coronation Hospital | Statement: [Rahima Moosa Mother and Child Hospital, formerName, Coronation Hospital]
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: Coronation Hospital
Triple: [Rahima Moosa Mother and Child Hospital, formerName, Coronation Hospital]
Generated description
Coronation Hospital was a major public healthcare facility in Johannesburg, South Africa, later renamed Rahima Moosa Mother and Child Hospital and known for serving women and children.

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_69eeeb52908c8190bd246244686aa455 completed April 27, 2026, 4:51 a.m.
NER Named-entity recognition batch_69f62196241c8190a52462f0f93b3998 completed May 2, 2026, 4:08 p.m.
NED1 Entity disambiguation (via context triple) batch_6a1229bc38388190b9dbcd7b168c7b2c completed May 23, 2026, 10:27 p.m.
NEDg Description generation batch_6a122a580e188190aeb20ac47d23e414 completed May 23, 2026, 10:29 p.m.
NED2 Entity disambiguation (via description) batch_6a122af21ba88190b6779cd1c12861a1 completed May 23, 2026, 10:32 p.m.
Created at: April 27, 2026, 6:56 a.m.