Triple

T27617008
Position Surface form Disambiguated ID Type / Status
Subject Sama of Tawi-Tawi E700464 entity
Predicate indigenousTo P3743 FINISHED
Object Tawi-Tawi archipelago
The Tawi-Tawi archipelago is a group of islands in the southern Philippines known for its predominantly Muslim communities, maritime culture, and strategic location near Malaysia and Indonesia.
E2020195 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: Tawi-Tawi archipelago | Statement: [Sama of Tawi-Tawi, indigenousTo, Tawi-Tawi archipelago]
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: Tawi-Tawi archipelago
Triple: [Sama of Tawi-Tawi, indigenousTo, Tawi-Tawi archipelago]
Generated description
The Tawi-Tawi archipelago is a group of islands in the southern Philippines known for its predominantly Muslim communities, maritime culture, and strategic location near Malaysia and Indonesia.

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_69ef6a4f1d9c8190b0705acda054368d completed April 27, 2026, 1:53 p.m.
NER Named-entity recognition batch_69f630d8fcc8819094fbd88f40b7230f completed May 2, 2026, 5:14 p.m.
NED1 Entity disambiguation (via context triple) batch_6a349e912c448190b00e68b77c82629d completed June 19, 2026, 1:42 a.m.
NEDg Description generation batch_6a349fe6eff08190a20885913ed7d166 completed June 19, 2026, 1:48 a.m.
NED2 Entity disambiguation (via description) batch_6a34a066b2808190acb2c406f93760d7 completed June 19, 2026, 1:50 a.m.
Created at: April 27, 2026, 2:13 p.m.