Triple

T25773259
Position Surface form Disambiguated ID Type / Status
Subject Philippine expressway network E649076 entity
Predicate hasComponent P35 FINISHED
Object CALAX Cavite section
The CALAX Cavite section is a major toll expressway segment in Cavite, Philippines, designed to improve connectivity between key urban and industrial areas and ease traffic congestion in the region.
E1694073 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: CALAX Cavite section | Statement: [Philippine expressway network, hasComponent, CALAX Cavite section]
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: CALAX Cavite section
Triple: [Philippine expressway network, hasComponent, CALAX Cavite section]
Generated description
The CALAX Cavite section is a major toll expressway segment in Cavite, Philippines, designed to improve connectivity between key urban and industrial areas and ease traffic congestion in the region.

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_69e7ab333b508190b6d708d8d9a328ed completed April 21, 2026, 4:52 p.m.
NER Named-entity recognition batch_69f5fe5b23ac81908ff1b6f06911f45b completed May 2, 2026, 1:38 p.m.
NED1 Entity disambiguation (via context triple) batch_6a10cc20f4d88190a9f1ddb294de8272 completed May 22, 2026, 9:35 p.m.
NEDg Description generation batch_6a10cde569f08190b5999538135c72a9 completed May 22, 2026, 9:43 p.m.
NED2 Entity disambiguation (via description) batch_6a10ce8ce9dc819097e693a12731bf5d completed May 22, 2026, 9:45 p.m.
Created at: April 22, 2026, 5:31 a.m.