Triple

T33839376
Position Surface form Disambiguated ID Type / Status
Subject Metro Manila road network E867317 entity
Predicate majorComponent P15759 FINISHED
Object Radial Road 10
Radial Road 10 is a key north–south arterial highway in Metro Manila that runs along the western side of the metropolis, connecting central Manila to northern suburban areas and port zones.
E2084403 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: Radial Road 10 | Statement: [Metro Manila road network, majorComponent, Radial Road 10]
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: Radial Road 10
Triple: [Metro Manila road network, majorComponent, Radial Road 10]
Generated description
Radial Road 10 is a key north–south arterial highway in Metro Manila that runs along the western side of the metropolis, connecting central Manila to northern suburban areas and port zones.

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_69f34992ad40819087760ed939bd2a7a completed April 30, 2026, 12:22 p.m.
NER Named-entity recognition batch_69f7004d97408190a3b09fa2bda3d42e completed May 3, 2026, 7:59 a.m.
NED1 Entity disambiguation (via context triple) batch_6a36c1ad0fac8190b84b6dbffd827eb1 completed June 20, 2026, 4:37 p.m.
NEDg Description generation batch_6a36c359f4e08190b516e4ac8ae687ff completed June 20, 2026, 4:44 p.m.
NED2 Entity disambiguation (via description) batch_6a36c532b54c8190a87547d1143dd7d2 completed June 20, 2026, 4:52 p.m.
Created at: May 1, 2026, 1:47 a.m.