Triple
T13088010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bataan |
E310386
|
entity |
| Predicate | hasMunicipality |
P847
|
FINISHED |
| Object | Morong |
E317276
|
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: Morong | Statement: [Bataan, hasMunicipality, Morong]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Morong Context triple: [Bataan, hasMunicipality, Morong]
-
A.
Morong
chosen
Morong is a coastal municipality in the Philippine province of Bataan known for its beaches, eco-tourism sites, and the Pawikan (sea turtle) Conservation Center.
-
B.
Morong
Morong is a coastal municipality in the Philippine province of Rizal known for its historic church and proximity to Metro Manila.
-
C.
Mogilany
Mogilany is a village in southern Poland that serves as the seat of Gmina Mogilany within the Lesser Poland Voivodeship.
-
D.
Malba
Malba is an affluent residential neighborhood in the northeastern part of Queens, New York City, known for its large waterfront homes and quiet, suburban character.
-
E.
Morro
Morro is a village located on the island of Maio in Cape Verde, known for its coastal setting and small-community character.
- 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_69d806a733548190989cfd4ce981ca33 |
completed | April 9, 2026, 8:05 p.m. |
| NER | Named-entity recognition | batch_69d981378dd08190b4f00e4e5df0e480 |
completed | April 10, 2026, 11:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f6d614704481908758cf8691a941ea |
completed | May 3, 2026, 4:59 a.m. |
Created at: April 9, 2026, 9:02 p.m.