Triple

T29276853
Position Surface form Disambiguated ID Type / Status
Subject National Police Commission E742265 entity
Predicate headquarters P62 FINISHED
Object EDSA corner Quezon Avenue, Quezon City
EDSA corner Quezon Avenue in Quezon City is a major urban intersection and landmark area in Metro Manila that hosts key government offices and heavy commuter traffic.
E1859808 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: EDSA corner Quezon Avenue, Quezon City | Statement: [National Police Commission, headquarters, EDSA corner Quezon Avenue, Quezon City]
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: EDSA corner Quezon Avenue, Quezon City
Triple: [National Police Commission, headquarters, EDSA corner Quezon Avenue, Quezon City]
Generated description
EDSA corner Quezon Avenue in Quezon City is a major urban intersection and landmark area in Metro Manila that hosts key government offices and heavy commuter traffic.

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_69f0912124d48190a046642b69407f4c completed April 28, 2026, 10:51 a.m.
NER Named-entity recognition batch_69f665122c9c8190bc72315f4ad39fa1 completed May 2, 2026, 8:56 p.m.
NED1 Entity disambiguation (via context triple) batch_6a25893d748c81909f427642cfa4f2cd completed June 7, 2026, 3:07 p.m.
NEDg Description generation batch_6a258e5fdc0c8190ac32db7404b5ef6c completed June 7, 2026, 3:29 p.m.
NED2 Entity disambiguation (via description) batch_6a2593a40fa48190b705582f4be60140 completed June 7, 2026, 3:52 p.m.
Created at: April 28, 2026, 12:51 p.m.