Triple

T35554254
Position Surface form Disambiguated ID Type / Status
Subject Iwahig Firefly Watching E1027448 entity
Predicate operatesOn P23 FINISHED
Object Iwahig River
Iwahig River is a scenic waterway in Puerto Princesa, Palawan, Philippines, known for its mangrove-lined banks and abundant firefly populations that attract nighttime river tours.
E2294265 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: Iwahig River | Statement: [Iwahig Firefly Watching, operatesOn, Iwahig River]
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: Iwahig River
Triple: [Iwahig Firefly Watching, operatesOn, Iwahig River]
Generated description
Iwahig River is a scenic waterway in Puerto Princesa, Palawan, Philippines, known for its mangrove-lined banks and abundant firefly populations that attract nighttime river tours.

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_69f76e014fd481909e9f04ac603a2aa9 completed May 3, 2026, 3:47 p.m.
NER Named-entity recognition batch_69f7983dad2c81908141e2cde597058e completed May 3, 2026, 6:47 p.m.
NED1 Entity disambiguation (via context triple) batch_6a7bc4cb63e08190b19c07316cd5f453 completed Aug. 12, 2026, 12:56 a.m.
NEDg Description generation batch_6a7bc544698881909292cb85a6d07fa9 completed Aug. 12, 2026, 12:58 a.m.
NED2 Entity disambiguation (via description) batch_6a7bc5a348408190a3286d7c58ccbf51 completed Aug. 12, 2026, 1 a.m.
Created at: May 3, 2026, 4:04 p.m.