Triple
T16122997
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Municipality of Mariveles |
E391191
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object | Poblacion |
E1033629
|
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: Poblacion | Statement: [Municipality of Mariveles, hasBarangay, Poblacion]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Poblacion Context triple: [Municipality of Mariveles, hasBarangay, Poblacion]
-
A.
Poblacion
Poblacion is the central urban barangay and main town center of Baler in Aurora province, Philippines.
-
B.
Poblacion
chosen
Poblacion is the central urban barangay and administrative core of the municipality of Morong in the province of Bataan, Philippines.
-
C.
Poblacion
Poblacion is the central urban barangay and administrative hub of the municipality of Argao in Cebu, Philippines.
-
D.
Poblacion
Poblacion is the central urban barangay and administrative hub of the municipality of Dumalag in the Philippines.
-
E.
Poblacion
Poblacion is a historic and nightlife-centric urban barangay in Makati, Metro Manila, known for its mix of old residential areas, bars, restaurants, and cultural spots.
- 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_69d87f1bb0988190b490d273dbf3fd03 |
completed | April 10, 2026, 4:39 a.m. |
| NER | Named-entity recognition | batch_69e202027e78819091192aa62aedde13 |
completed | April 17, 2026, 9:48 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fff2a7fe308190a9a2ef7815e788c6 |
completed | May 10, 2026, 2:51 a.m. |
Created at: April 10, 2026, 5 a.m.