Triple
T11572940
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oton |
E274434
|
entity |
| Predicate | hasBarangay |
P29835
|
FINISHED |
| Object | Malingin |
E906334
|
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: Malingin | Statement: [Oton, hasBarangay, Malingin]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Malingin Context triple: [Oton, hasBarangay, Malingin]
-
A.
Malingin
chosen
Malingin is a barangay (village-level administrative division) of the municipality of Daanbantayan in Cebu, Philippines.
-
B.
Malumfashi
Malumfashi is a town and local government area in northern Nigeria known for its role as an administrative and commercial center within Katsina State.
-
C.
Putatan
Putatan is a barangay and residential district within the city of Muntinlupa in Metro Manila, Philippines.
-
D.
Małdyty
Małdyty is a village and administrative center in northern Poland, situated in the Warmian-Masurian Voivodeship and known for its proximity to the region’s lakes and forests.
-
E.
Malakula
Malakula is one of the largest and most culturally diverse islands of Vanuatu, known for its many distinct languages and traditional customs.
- 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_69d6aae5ac3c81908d2b0a3a665665b2 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d88dd6913881908becf188c0a7a275 |
completed | April 10, 2026, 5:42 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e713d18ccc8190a63256c3cc1c2f59 |
completed | April 21, 2026, 6:06 a.m. |
Created at: April 8, 2026, 9:38 p.m.