Triple
T2369950
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pasig River |
E46063
|
entity |
| Predicate | flowsThrough |
P225
|
FINISHED |
| Object | Taguig |
E104725
|
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: Taguig | Statement: [Pasig River, flowsThrough, Taguig]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taguig Context triple: [Pasig River, flowsThrough, Taguig]
-
A.
Taguig
chosen
Taguig is a highly urbanized city in Metro Manila in the Philippines, known for the Bonifacio Global City (BGC) business district and rapid commercial and residential development.
-
B.
Malabon
Malabon is a coastal city in the northern part of Metro Manila in the Philippines, known for its historic districts, flood-prone waterways, and distinctive local cuisine.
-
C.
Muntinlupa
Muntinlupa is a highly urbanized city in the southern part of Metro Manila in the Philippines, known for housing the New Bilibid Prison and major commercial and residential developments like Alabang.
-
D.
Mandaluyong
Mandaluyong is a highly urbanized city in the Philippines known as part of Metro Manila’s central business and commercial district.
-
E.
Bacoor
Bacoor is a coastal city in the province of Cavite in the Philippines, situated just south of Metro Manila along the shores of Manila Bay.
- 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_69a88a145268819083e2736cb835c696 |
completed | March 4, 2026, 7:37 p.m. |
| NER | Named-entity recognition | batch_69abc76f5aec8190867d621e6849258c |
completed | March 7, 2026, 6:36 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69aef094fd8081909fc9a19f3e36c0d0 |
completed | March 9, 2026, 4:08 p.m. |
Created at: March 4, 2026, 7:56 p.m.