Triple

T28429239
Position Surface form Disambiguated ID Type / Status
Subject Ditumabo Mother Falls E715072 entity
Predicate hasAlternateName P39 FINISHED
Object Mother Falls
Mother Falls is a popular and scenic waterfall in Baler, Aurora, Philippines, known for its tall cascade, lush forest surroundings, and refreshing natural pool.
 E1918050 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: Mother Falls | Statement: [Ditumabo Mother Falls, hasAlternateName, Mother Falls]
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: Mother Falls
Triple: [Ditumabo Mother Falls, hasAlternateName, Mother Falls]
Generated description
Mother Falls is a popular and scenic waterfall in Baler, Aurora, Philippines, known for its tall cascade, lush forest surroundings, and refreshing natural pool.

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_69efd6b253888190b3c7222ed6a403a8 completed April 27, 2026, 9:35 p.m.
NER Named-entity recognition batch_69f64dffeda081909a61d05295bf0862 completed May 2, 2026, 7:18 p.m.
NED1 Entity disambiguation (via context triple) batch_6a27abf4a9bc8190b5236993d9f55ff5 completed June 9, 2026, 6 a.m.
NEDg Description generation batch_6a27ae1a3784819097722737c0b949cb completed June 9, 2026, 6:09 a.m.
NED2 Entity disambiguation (via description) batch_6a27aef0046081908c95ec0fa0e0497d completed June 9, 2026, 6:13 a.m.
Created at: April 28, 2026, 1:38 a.m.