Triple

T5357781
Position Surface form Disambiguated ID Type / Status
Subject La Mesa Watershed E102741 entity
Predicate locatedNear P294 FINISHED
Object Novaliches
Novaliches is a suburban district in northern Metro Manila, Philippines, known for its mixed residential and commercial areas and proximity to major water and nature reserves.
 E514274 NE FINISHED

How this triple was built (4 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: Novaliches | Statement: [La Mesa Watershed, locatedNear, Novaliches]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07 
Target entity: Novaliches
Context triple: [La Mesa Watershed, locatedNear, Novaliches]
  • A. Lechmere
    Lechmere is a Massachusetts Bay Transportation Authority (MBTA) light rail station in Cambridge, Massachusetts, serving the Green Line.
  • B. Thyez
    Thyez is a commune in the Haute-Savoie department of southeastern France, situated in the Alps near the town of Bonneville.
  • C. Balivanich
    Balivanich is the main village and administrative center on the island of Benbecula in Scotland’s Outer Hebrides.
  • D. Tavium
    Tavium was an important ancient city of the Galatian Celts in central Anatolia, serving as a key political and commercial center.
  • E. Kierling
    Kierling is a small locality in Lower Austria best known as the place where writer Franz Kafka spent his final days and died.
  • F. None of above. chosen
  • G. Unsure - the case is ambiguous/there is not enough information to decide.
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: Novaliches
Triple: [La Mesa Watershed, locatedNear, Novaliches]
Generated description
Novaliches is a suburban district in northern Metro Manila, Philippines, known for its mixed residential and commercial areas and proximity to major water and nature reserves.
NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07 
Target entity: Novaliches
Target entity description: Novaliches is a suburban district in northern Metro Manila, Philippines, known for its mixed residential and commercial areas and proximity to major water and nature reserves.
  • A. Lechmere
    Lechmere is a Massachusetts Bay Transportation Authority (MBTA) light rail station in Cambridge, Massachusetts, serving the Green Line.
  • B. Thyez
    Thyez is a commune in the Haute-Savoie department of southeastern France, situated in the Alps near the town of Bonneville.
  • C. Balivanich
    Balivanich is the main village and administrative center on the island of Benbecula in Scotland’s Outer Hebrides.
  • D. Tavium
    Tavium was an important ancient city of the Galatian Celts in central Anatolia, serving as a key political and commercial center.
  • E. Kierling
    Kierling is a small locality in Lower Austria best known as the place where writer Franz Kafka spent his final days and died.
  • F. None of above. chosen

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_69bd43d8f7248190b64c140734b5c9a8 completed March 20, 2026, 12:55 p.m.
NER Named-entity recognition batch_69bd863099b081909d20f7014b98de5a completed March 20, 2026, 5:38 p.m.
NED1 Entity disambiguation (via context triple) batch_69bf21e6762481909278935a4eeee177 completed March 21, 2026, 10:55 p.m.
NEDg Description generation batch_69bf228956d481909e9f3c11f4597cce completed March 21, 2026, 10:58 p.m.
NED2 Entity disambiguation (via description) batch_69bf230b571481909f76ada72d94c8d8 completed March 21, 2026, 11 p.m.
Created at: March 20, 2026, 2:01 p.m.