Triple

T32494572
Position Surface form Disambiguated ID Type / Status
Subject T.M. Kalaw Street E830483 entity
Predicate hasFormerName P65 FINISHED
Object Cavendish Street
Cavendish Street was the former name of what is now known as T.M. Kalaw Street in Manila, Philippines, a significant thoroughfare in the city's Ermita district.
 E2291504 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: Cavendish Street | Statement: [T.M. Kalaw Street, hasFormerName, Cavendish Street]
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: Cavendish Street
Triple: [T.M. Kalaw Street, hasFormerName, Cavendish Street]
Generated description
Cavendish Street was the former name of what is now known as T.M. Kalaw Street in Manila, Philippines, a significant thoroughfare in the city's Ermita district.

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_69f34920aa4081908d8fb0277414b911 completed April 30, 2026, 12:20 p.m.
NER Named-entity recognition batch_69f6c409752081909622d522bbac6557 completed May 3, 2026, 3:42 a.m.
NED1 Entity disambiguation (via context triple) batch_6a5c6460e1648190a2d0633a27ed2553 completed July 19, 2026, 5:45 a.m.
NEDg Description generation batch_6a5c658742248190ab84c4a4e71f5b88 completed July 19, 2026, 5:49 a.m.
NED2 Entity disambiguation (via description) batch_6a5c65ab73a481908a0e3285bb178459 completed July 19, 2026, 5:50 a.m.
Created at: May 1, 2026, 12:59 a.m.