Triple
T8079548
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NCR |
E188578
|
entity |
| Predicate | contains |
P35
|
FINISHED |
| Object | Las Piñas |
E213931
|
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: Las Piñas | Statement: [NCR, contains, Las Piñas]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Las Piñas Context triple: [NCR, contains, Las Piñas]
-
A.
Las Piñas
chosen
Las Piñas is a highly urbanized city in the southern part of Metro Manila in the Philippines, known for its residential communities and the historic Bamboo Organ.
-
B.
Carmona
Carmona is a municipality in the province of Cavite in the Philippines, known for its mix of residential communities and industrial estates.
-
C.
Carmona
Carmona is a historic town in southern Spain renowned for its well-preserved medieval and Moorish architecture, including ancient city walls and hilltop fortifications.
-
D.
Sta. Cruz
Sta. Cruz is a coastal municipality in the province of Zambales in the Philippines, known for its fishing communities and proximity to the West Philippine Sea.
-
E.
Dasmariñas
Dasmariñas is a rapidly urbanizing city in the province of Cavite in the Philippines, known as a major residential, commercial, and educational hub south of Metro Manila.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69ca82b662e88190b9323daab8c28a21 |
completed | March 30, 2026, 2:03 p.m. |
| NER | Named-entity recognition | batch_69cb40a3f01c819096a2c9d5d5199fe6 |
completed | March 31, 2026, 3:33 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cc93eddef48190b5f499a5b52428c8 |
completed | April 1, 2026, 3:41 a.m. |
Created at: March 30, 2026, 5:28 p.m.