Triple

T30254362
Position Surface form Disambiguated ID Type / Status
Subject The City of Heroes E769295 entity
Predicate hasAlternativeName P39 FINISHED
Object Lungsod ng mga Bayani
Lungsod ng mga Bayani is a Filipino moniker meaning "City of Heroes," commonly used to honor a place renowned for its historic role and the heroism of its people.
E1905903 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: Lungsod ng mga Bayani | Statement: [The City of Heroes, hasAlternativeName, Lungsod ng mga Bayani]
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: Lungsod ng mga Bayani
Triple: [The City of Heroes, hasAlternativeName, Lungsod ng mga Bayani]
Generated description
Lungsod ng mga Bayani is a Filipino moniker meaning "City of Heroes," commonly used to honor a place renowned for its historic role and the heroism of its people.

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_69f224831dc08190b2e569b987264057 completed April 29, 2026, 3:32 p.m.
NER Named-entity recognition batch_69f6807e374881909a0c7edfde2e8f35 completed May 2, 2026, 10:53 p.m.
NED1 Entity disambiguation (via context triple) batch_6a2764576dc081909ed06914644d7b59 completed June 9, 2026, 12:54 a.m.
NEDg Description generation batch_6a276576a8088190acca28b607d0fb41 completed June 9, 2026, 12:59 a.m.
NED2 Entity disambiguation (via description) batch_6a2766aef0c08190ad736595abed58f3 completed June 9, 2026, 1:04 a.m.
Created at: April 29, 2026, 7:40 p.m.