Triple

T28308425
Position Surface form Disambiguated ID Type / Status
Subject Penang Free School E713929 entity
Predicate currentAddress P170808 FINISHED
Object Green Lane, George Town, Penang
Green Lane in George Town, Penang is a major suburban thoroughfare and residential area known for housing prominent institutions and schools.
 E1811248 NE FINISHED

How this triple was built (3 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: Green Lane, George Town, Penang | Statement: [Penang Free School, currentAddress, Green Lane, George Town, Penang]
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: Green Lane, George Town, Penang
Triple: [Penang Free School, currentAddress, Green Lane, George Town, Penang]
Generated description
Green Lane in George Town, Penang is a major suburban thoroughfare and residential area known for housing prominent institutions and schools.
PD Predicate disambiguation gpt-5-mini-2025-08-07 
Target predicate: currentAddress
Context triple: [Penang Free School, currentAddress, Green Lane, George Town, Penang]
  • A. streetAddressNow chosen
    Indicates that an entity’s current street address is the specified location.
  • B. locationAddressed
    Indicates that a communication, message, or action is specifically directed to or intended for a particular location or address.
  • C. currentlyLocatedAt
    Indicates that an entity’s present or most recent known physical location is at the specified place.
  • D. address
    Indicates that one entity directs spoken or written communication specifically to another entity.
  • E. streetAddress
    Indicates the specific location of an entity in terms of its numbered building and street name within a postal address.
  • F. None of above.

Provenance (6 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_69efb5256afc8190b9322d25c3ae6320 completed April 27, 2026, 7:12 p.m.
NER Named-entity recognition batch_69fcf825ca7081909d06b0df33eb33f9 completed May 7, 2026, 8:37 p.m.
NED1 Entity disambiguation (via context triple) batch_6a16073aba50819091421bd46a4c2382 completed May 26, 2026, 8:48 p.m.
NEDg Description generation batch_6a161461afac81909c4f6f35530f73de completed May 26, 2026, 9:45 p.m.
NED2 Entity disambiguation (via description) batch_6a161524fd648190b932ebe251413aa3 completed May 26, 2026, 9:48 p.m.
PD Predicate disambiguation batch_69fcf42160f0819096812a8bf590875e completed May 7, 2026, 8:20 p.m.
Created at: April 27, 2026, 11:39 p.m.