Triple
T18550379
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gil Puyat Avenue |
E453357
|
entity |
| Predicate | locatedIn |
P40
|
FINISHED |
| Object | Pasay |
—
|
NE NERFINISHED |
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: Pasay | Statement: [Gil Puyat Avenue, locatedIn, Pasay]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Pasay Context triple: [Gil Puyat Avenue, locatedIn, Pasay]
-
A.
Pasay
chosen
Pasay is a highly urbanized coastal city in the Philippines known for its entertainment complexes, shopping centers, and proximity to Manila’s main international airport.
-
B.
Malpaso
Malpaso is the highest peak on the Canary Island of El Hierro, known for its panoramic views over the island and surrounding Atlantic Ocean.
-
C.
Tanjay
Tanjay is a component city in the province of Negros Oriental in the Philippines, known for its agricultural economy and cultural festivals.
-
D.
Plaridel
Plaridel is a municipality in the province of Bulacan in the Philippines, known for its historical significance and proximity to Metro Manila.
-
E.
Plaridel
Plaridel is a barangay (village-level administrative division) within the city of Sagay in the Philippines.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d388b0c881908e610a1c45b52640 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e53800c0fc819097782f1e81574598 |
completed | April 19, 2026, 8:16 p.m. |
Created at: April 10, 2026, 11:38 a.m.